Alternatives to Apache HBase

Redis Labs is the home of Redis. Redis Enterprise is the best Redis version. Redis Enterprise is more than a cache. Redis Enterprise can be free in the cloud with NoSQL and data caching using the fastest in-memory database. Redis can be scaled, enterprise-grade resilience, massive scaling, ease of administration, and operational simplicity. Redis in the Cloud is a favorite of DevOps. Developers have access to enhanced data structures and a variety modules. This allows them to innovate faster and has a faster time-to-market. CIOs love the security and expert support of Redis, which provides 99.999% uptime. Use relational databases for active-active, geodistribution, conflict distribution, reads/writes in multiple regions to the same data set. Redis Enterprise offers flexible deployment options. Redis Labs is the home of Redis. Redis JSON, Redis Java, Python Redis, Redis on Kubernetes & Redis gui best practices.

RavenDB is a pioneering NoSQL Document Database. It is fully transactional (ACID across your database and within your cluster). Our open-source distributed database has high availability and high performance, with minimal administration. It is an all-in-one database that is easy to use. This reduces the need to add on tools or support for developers to increase developer productivity and speed up your project's production. In minutes, you can create and secure a data cluster and deploy it in the cloud, on-premise, or in a hybrid environment. RavenDB offers a Database as a Service, which allows you to delegate all database operations to us, so you can concentrate on your application. RavenDB's built-in storage engine Voron can perform at speeds of up to 1,000,000 reads per second and 150,000 write per second on a single node. This allows you to improve your application's performance by using simple commodity hardware.

Amazon DynamoDB is a versatile key-value and document database that provides exceptional single-digit millisecond performance, regardless of scale. As a fully managed service, it offers multi-region, multimaster durability along with integrated security features, backup and restore capabilities, and in-memory caching designed for internet-scale applications. With the ability to handle over 10 trillion requests daily and support peak loads exceeding 20 million requests per second, it serves a wide range of businesses. Prominent companies like Lyft, Airbnb, and Redfin, alongside major enterprises such as Samsung, Toyota, and Capital One, rely on DynamoDB for their critical operations, leveraging its scalability and performance. This allows organizations to concentrate on fostering innovation without the burden of operational management. You can create an immersive gaming platform that manages player data, session histories, and leaderboards for millions of users simultaneously. Additionally, it facilitates the implementation of design patterns for various applications like shopping carts, workflow engines, inventory management, and customer profiles. DynamoDB is well-equipped to handle high-traffic, large-scale events seamlessly, making it an ideal choice for modern applications.

When seeking a database that ensures both scalability and high availability without sacrificing performance, Apache Cassandra stands out as an ideal option. Its linear scalability paired with proven fault tolerance on standard hardware or cloud services positions it as an excellent choice for handling mission-critical data effectively. Additionally, Cassandra's superior capability to replicate data across several datacenters not only enhances user experience by reducing latency but also offers reassurance in the event of regional failures. This combination of features makes it a robust solution for organizations that prioritize data resilience and efficiency.

Amazon Redshift is the preferred choice among customers for cloud data warehousing, outpacing all competitors in popularity. It supports analytical tasks for a diverse range of organizations, from Fortune 500 companies to emerging startups, facilitating their evolution into large-scale enterprises, as evidenced by Lyft's growth. No other data warehouse simplifies the process of extracting insights from extensive datasets as effectively as Redshift. Users can perform queries on vast amounts of structured and semi-structured data across their operational databases, data lakes, and the data warehouse using standard SQL queries. Moreover, Redshift allows for the seamless saving of query results back to S3 data lakes in open formats like Apache Parquet, enabling further analysis through various analytics services, including Amazon EMR, Amazon Athena, and Amazon SageMaker. Recognized as the fastest cloud data warehouse globally, Redshift continues to enhance its performance year after year. For workloads that demand high performance, the new RA3 instances provide up to three times the performance compared to any other cloud data warehouse available today, ensuring businesses can operate at peak efficiency. This combination of speed and user-friendly features makes Redshift a compelling choice for organizations of all sizes.

A Kudu cluster comprises tables that resemble those found in traditional relational (SQL) databases. These tables can range from a straightforward binary key and value structure to intricate designs featuring hundreds of strongly-typed attributes. Similar to SQL tables, each Kudu table is defined by a primary key, which consists of one or more columns; this could be a single unique user identifier or a composite key such as a (host, metric, timestamp) combination tailored for time-series data from machines. The primary key allows for quick reading, updating, or deletion of rows. The straightforward data model of Kudu facilitates the migration of legacy applications as well as the development of new ones, eliminating concerns about encoding data into binary formats or navigating through cumbersome JSON databases. Additionally, tables in Kudu are self-describing, enabling the use of standard analysis tools like SQL engines or Spark. With user-friendly APIs, Kudu ensures that developers can easily integrate and manipulate their data. This approach not only streamlines data management but also enhances overall efficiency in data processing tasks.

Apache Hive is a data warehouse solution that enables the efficient reading, writing, and management of substantial datasets stored across distributed systems using SQL. It allows users to apply structure to pre-existing data in storage. To facilitate user access, it comes equipped with a command line interface and a JDBC driver. As an open-source initiative, Apache Hive is maintained by dedicated volunteers at the Apache Software Foundation. Initially part of the Apache® Hadoop® ecosystem, it has since evolved into an independent top-level project. We invite you to explore the project further and share your knowledge to enhance its development. Users typically implement traditional SQL queries through the MapReduce Java API, which can complicate the execution of SQL applications on distributed data. However, Hive simplifies this process by offering a SQL abstraction that allows for the integration of SQL-like queries, known as HiveQL, into the underlying Java framework, eliminating the need to delve into the complexities of the low-level Java API. This makes working with large datasets more accessible and efficient for developers.

Google Cloud Bigtable provides a fully managed, scalable NoSQL data service that can handle large operational and analytical workloads. Cloud Bigtable is fast and performant. It's the storage engine that grows with your data, from your first gigabyte up to a petabyte-scale for low latency applications and high-throughput data analysis. Seamless scaling and replicating: You can start with one cluster node and scale up to hundreds of nodes to support peak demand. Replication adds high availability and workload isolation to live-serving apps. Integrated and simple: Fully managed service that easily integrates with big data tools such as Dataflow, Hadoop, and Dataproc. Development teams will find it easy to get started with the support for the open-source HBase API standard.

Couchbase distinguishes itself from other NoSQL databases by delivering an enterprise-grade, multicloud to edge solution that is equipped with the powerful features essential for mission-critical applications on a platform that is both highly scalable and reliable. This distributed cloud-native database operates seamlessly in contemporary dynamic settings, accommodating any cloud environment, whether it be customer-managed or a fully managed service. Leveraging open standards, Couchbase merges the advantages of NoSQL with the familiar structure of SQL, thereby facilitating a smoother transition from traditional mainframe and relational databases. Couchbase Server serves as a versatile, distributed database that integrates the benefits of relational database capabilities, including SQL and ACID transactions, with the adaptability of JSON, all built on a foundation that is remarkably fast and scalable. Its applications span various industries, catering to needs such as user profiles, dynamic product catalogs, generative AI applications, vector search, high-speed caching, and much more, making it an invaluable asset for organizations seeking efficiency and innovation.

Introducing a versatile, open-source multi-cloud platform for contemporary data applications, built on Apache Cassandra™. Achieve global-scale performance with guaranteed 100% uptime while avoiding vendor lock-in. You have the flexibility to deploy on multi-cloud environments, on-premises infrastructures, or use Kubernetes. The platform is designed to be elastic and offers a pay-as-you-go pricing model to enhance total cost of ownership. Accelerate your development process with Stargate APIs, which support NoSQL, real-time interactions, reactive programming, as well as JSON, REST, and GraphQL formats. Bypass the difficulties associated with managing numerous open-source projects and APIs that lack scalability. This solution is perfect for various sectors including e-commerce, mobile applications, AI/ML, IoT, microservices, social networking, gaming, and other highly interactive applications that require dynamic scaling based on demand. Start your journey of creating modern data applications with Astra, a database-as-a-service powered by Apache Cassandra™. Leverage REST, GraphQL, and JSON alongside your preferred full-stack framework. This platform ensures that your richly interactive applications are not only elastic but also ready to gain traction from the very first day, all while offering a cost-effective Apache Cassandra DBaaS that scales seamlessly and affordably as your needs evolve. With this innovative approach, developers can focus on building rather than managing infrastructure.

Hypertable provides a high-performance, scalable database solution that enhances the efficiency of your big data applications while minimizing hardware usage. This platform offers exceptional efficiency and outperforms its competitors, leading to significant cost reductions for users. Its robust and proven architecture supports numerous services at Google. Users can enjoy the advantages of open-source technology backed by a vibrant and active community. With a C++ implementation, Hypertable ensures optimal performance. Additionally, it offers around-the-clock support for critical big data operations. Clients benefit from direct access to the expertise of the core developers behind Hypertable. Specifically engineered to address scalability challenges that traditional relational database management systems struggle with, Hypertable leverages a design model pioneered by Google to effectively tackle scaling issues, making it superior to other NoSQL alternatives available today. Its innovative approach not only resolves current scalability needs but also anticipates future demands in data management.

Utilize Azure Table storage to manage petabytes of semi-structured data efficiently while keeping expenses low. In contrast to various data storage solutions, whether local or cloud-based, Table storage enables seamless scaling without the need for manual sharding of your dataset. Additionally, concerns about data availability are mitigated through the use of geo-redundant storage, which ensures that data is replicated three times within a single region and an extra three times in a distant region, enhancing data resilience. This storage option is particularly advantageous for accommodating flexible datasets—such as user data from web applications, address books, device details, and various other types of metadata—allowing you to develop cloud applications without restricting the data model to specific schemas. Each row in a single table can possess a unique structure, for instance, featuring order details in one entry and customer data in another, which grants you the flexibility to adapt your application and modify the table schema without requiring downtime. Furthermore, Table storage is designed with a robust consistency model to ensure reliable data access. Overall, it provides an adaptable and scalable solution for modern data management needs.

ScyllaDB serves as an ideal database solution for applications that demand high performance and minimal latency, catering specifically to data-intensive needs. It empowers teams to fully utilize the growing computing capabilities of modern infrastructures, effectively removing obstacles to scaling as data volumes expand. Distinct from other database systems, ScyllaDB stands out as a distributed NoSQL database that is completely compatible with both Apache Cassandra and Amazon DynamoDB, while incorporating significant architectural innovations that deliver outstanding user experiences at significantly reduced costs. Over 400 transformative companies, including Disney+ Hotstar, Expedia, FireEye, Discord, Zillow, Starbucks, Comcast, and Samsung, rely on ScyllaDB to tackle their most challenging database requirements. Furthermore, ScyllaDB is offered in various formats, including a free open-source version, a fully-supported enterprise solution, and a fully managed database-as-a-service (DBaaS) available across multiple cloud platforms, ensuring flexibility for diverse user needs. This versatility makes it an attractive choice for organizations looking to optimize their database performance.

ClickHouse is an efficient, open-source OLAP database management system designed for high-speed data processing. Its column-oriented architecture facilitates the creation of analytical reports through real-time SQL queries. In terms of performance, ClickHouse outshines similar column-oriented database systems currently on the market. It has the capability to handle hundreds of millions to over a billion rows, as well as tens of gigabytes of data, on a single server per second. By maximizing the use of available hardware, ClickHouse ensures rapid query execution. The peak processing capacity for individual queries can exceed 2 terabytes per second, considering only the utilized columns after decompression. In a distributed environment, read operations are automatically optimized across available replicas to minimize latency. Additionally, ClickHouse features multi-master asynchronous replication, enabling deployment across various data centers. Each node operates equally, effectively eliminating potential single points of failure and enhancing overall reliability. This robust architecture allows organizations to maintain high availability and performance even under heavy workloads.

This robust enterprise platform, built on Apache Ignite, delivers lightning-fast in-memory performance and extensive scalability for data-heavy applications, ensuring real-time access across various datastores and applications. Transitioning from Ignite to GridGain requires no code modifications, allowing for secure deployment of clusters on a global scale without experiencing any downtime. You can conduct rolling upgrades on your production clusters without affecting application availability, and replicate data across geographically dispersed data centers to balance workloads and mitigate the risk of outages in specific regions. Your data remains secure both at rest and in transit, while compliance with security and privacy regulations is guaranteed. Seamless integration with your organization’s existing authentication and authorization frameworks is straightforward, and comprehensive auditing of data and user activities can be enabled. Additionally, you can establish automated schedules for both full and incremental backups, ensuring that restoring your cluster to its most stable state is achievable through snapshots and point-in-time recovery. This platform not only promotes efficiency but also enhances resilience and security for all data operations.

Azure Cosmos DB offers a fully managed NoSQL database solution tailored for contemporary application development, ensuring single-digit millisecond response times and an impressive availability rate of 99.999 percent, all supported by service level agreements. This service provides automatic, instantaneous scalability and supports open-source APIs for MongoDB and Cassandra, allowing for rapid data operations. With its turnkey multi-master global distribution, users can experience swift read and write operations from any location around the globe. Additionally, Azure Cosmos DB enables organizations to accelerate their decision-making processes by facilitating near-real-time analytics and AI capabilities on the operational data housed within the database. Furthermore, Azure Synapse Link for Azure Cosmos DB integrates effortlessly with Azure Synapse Analytics, ensuring smooth performance without necessitating data movement or compromising the efficiency of the operational data store, enhancing the overall functionality of your data strategy. This integration not only streamlines workflows but also empowers users to derive insights more efficiently.

Apache Accumulo enables users to efficiently store and manage extensive data sets across a distributed cluster. It relies on Apache Hadoop's HDFS for data storage and utilizes Apache ZooKeeper to achieve consensus among nodes. While many users engage with Accumulo directly, it also serves as a foundational data store for various open-source projects. To gain deeper insights into Accumulo, you can explore the Accumulo tour, consult the user manual, and experiment with the provided example code. Should you have any inquiries, please do not hesitate to reach out to us. Accumulo features a programming mechanism known as Iterators, which allows for the modification of key/value pairs at different stages of the data management workflow. Each key/value pair within Accumulo is assigned a unique security label that restricts query outcomes based on user permissions. The system operates on a cluster configuration that can incorporate one or more HDFS instances, providing flexibility as data storage needs evolve. Additionally, nodes within the cluster can be dynamically added or removed in response to changes in the volume of data stored, enhancing scalability and resource management.

InfinityDB Embedded is a NoSQL database written in Java, designed as a hierarchical sorted key-value store. Its features include high performance, multi-core capability, flexibility, and a maintenance-free operation. In addition to the embedded version, InfinityDB now offers an Encrypted database and a Client/Server database. Customer feedback and performance evaluations indicate that InfinityDB delivers the highest performance in its class: its multi-core overlapping operations demonstrate nearly linear scalability with thread count, employ fair scheduling, and maintain very low inter-thread interference. Furthermore, random I/O performance improves logarithmically with file size, with no upper limit on size, while caches expand only as necessary and are efficiently packed. Notably, opening the database is instantaneous, even after an unexpected shutdown, ensuring minimal downtime and quick recovery. With these attributes, InfinityDB stands out as a top choice for developers seeking reliability and speed in their database solutions.

Aerospike is the global leader for next-generation, real time NoSQL data solutions at any scale. Aerospike helps enterprises overcome seemingly impossible data bottlenecks and compete with other companies at a fraction of the cost and complexity of legacy NoSQL databases. Aerospike's Hybrid Memory Architecture™ is a patented technology that unlocks the full potential of modern hardware and delivers previously unimaginable value. It does this by delivering unimaginable value from huge amounts of data at both the edge, core, and in the cloud. Aerospike empowers customers with the ability to instantly combat fraud, dramatically increase shopping cart sizes, deploy global digital payment networks, and provide instant, one-to-1 personalization for millions. Aerospike customers include Airtel and Banca d'Italia as well as Snap, Verizon Media, Wayfair, PayPal, Snap, Verizon Media, and Nielsen. The company's headquarters is in Mountain View, California. Additional locations are in London, Bengaluru, India, and Tel Aviv in Israel.

FoundationDB operates as a multi-model database, enabling the storage of various data types within a single system. Its Key-Value Store component ensures that all information is securely stored, distributed, and replicated. The installation, scaling, and management of FoundationDB are straightforward, benefiting from a distributed architecture that effectively scales and handles failures while maintaining the behavior of a singular ACID database. It delivers impressive performance on standard hardware, making it capable of managing substantial workloads at a minimal cost. With years of production use, FoundationDB has been reinforced through practical experience and insights gained over time. Additionally, its backup system is unparalleled, utilizing a deterministic simulation engine for testing purposes. We invite you to become an active member of our open-source community, where you can engage in both technical and user discussions on our forums and discover ways to contribute to the project. Your involvement can help shape the future of FoundationDB!

Riak is a distributed systems expert and works with Application teams to overcome distributed system challenges. Riak's Riak®, a distributed NoSQL databank, delivers: Unmatched resilience beyond the typical "high availability" offerings - Innovative technology to ensure data accuracy, and never lose a word. - Massive scale for commodity hardware - A common code foundation that supports true multi-model support Riak®, offers all of this while still focusing on ease-of-use. Choose Riak®, KV flexible key value data model for web scale profile management, session management, real time big data, catalog content management, customer 360, digital message and other use cases. Choose Riak®, TS for IoT, time series and other use cases.

Utilize Ignite as a conventional SQL database by employing JDBC drivers, ODBC drivers, or the dedicated SQL APIs that cater to Java, C#, C++, Python, and various other programming languages. Effortlessly perform operations such as joining, grouping, aggregating, and ordering your distributed data, whether it is stored in memory or on disk. By integrating Ignite as an in-memory cache or data grid across multiple external databases, you can enhance the performance of your existing applications by a factor of 100. Envision a cache that allows for SQL querying, transactional operations, and computational tasks. Develop contemporary applications capable of handling both transactional and analytical workloads by leveraging Ignite as a scalable database that exceeds the limits of available memory. Ignite smartly allocates memory for frequently accessed data and resorts to disk storage when dealing with less frequently accessed records. This allows for the execution of kilobyte-sized custom code across vast petabytes of data. Transform your Ignite database into a distributed supercomputer, optimized for rapid calculations, intricate analytics, and machine learning tasks, ensuring that your applications remain responsive and efficient even under heavy loads. Embrace the potential of Ignite to revolutionize your data processing capabilities and drive innovation within your projects.

What makes eXtremeDB platform independent? - Hybrid storage of data. Unlike other IMDS databases, eXtremeDB databases are all-in-memory or all-persistent. They can also have a mix between persistent tables and in-memory table. eXtremeDB's Active Replication Fabric™, which is unique to eXtremeDB, offers bidirectional replication and multi-tier replication (e.g. edge-to-gateway-to-gateway-to-cloud), compression to maximize limited bandwidth networks and more. - Row and columnar flexibility for time series data. eXtremeDB supports database designs which combine column-based and row-based layouts in order to maximize the CPU cache speed. - Client/Server and embedded. eXtremeDB provides data management that is fast and flexible wherever you need it. It can be deployed as an embedded system and/or as a clients/server database system. eXtremeDB was designed for use in resource-constrained, mission-critical embedded systems. Found in over 30,000,000 deployments, from routers to satellites and trains to stock market world-wide.

Greenplum Database® stands out as a sophisticated, comprehensive, and open-source data warehouse solution. It excels in providing swift and robust analytics on data volumes that reach petabyte scales. Designed specifically for big data analytics, Greenplum Database is driven by a highly advanced cost-based query optimizer that ensures exceptional performance for analytical queries on extensive data sets. This project operates under the Apache 2 license, and we extend our gratitude to all current contributors while inviting new ones to join our efforts. In the Greenplum Database community, every contribution is valued, regardless of its size, and we actively encourage diverse forms of involvement. This platform serves as an open-source, massively parallel data environment tailored for analytics, machine learning, and artificial intelligence applications. Users can swiftly develop and implement models aimed at tackling complex challenges in fields such as cybersecurity, predictive maintenance, risk management, and fraud detection, among others. Dive into the experience of a fully integrated, feature-rich open-source analytics platform that empowers innovation.

Parquet was developed to provide the benefits of efficient, compressed columnar data representation to all projects within the Hadoop ecosystem. Designed with a focus on accommodating complex nested data structures, Parquet employs the record shredding and assembly technique outlined in the Dremel paper, which we consider to be a more effective strategy than merely flattening nested namespaces. This format supports highly efficient compression and encoding methods, and various projects have shown the significant performance improvements that arise from utilizing appropriate compression and encoding strategies for their datasets. Furthermore, Parquet enables the specification of compression schemes at the column level, ensuring its adaptability for future developments in encoding technologies. It is crafted to be accessible for any user, as the Hadoop ecosystem comprises a diverse range of data processing frameworks, and we aim to remain neutral in our support for these different initiatives. Ultimately, our goal is to empower users with a flexible and robust tool that enhances their data management capabilities across various applications.

IBM Cloudant® is a robust distributed database tailored for managing the demanding workloads commonly associated with large, rapidly expanding web and mobile applications. Offered as a fully managed service on IBM Cloud™, backed by an SLA, Cloudant allows for the independent scaling of both throughput and storage. You can quickly deploy an instance, set up databases, and adjust throughput capacity and data storage as needed to align with your application’s demands. Furthermore, it ensures data security through encryption, providing optional user-defined key management via IBM Key Protect, while also allowing integration with IBM Identity and Access Management. With a focus on performance and disaster recovery, Cloudant guarantees continuous availability by distributing data across multiple availability zones and six regions, making it an ideal choice for critical applications. This distribution not only enhances app performance but also safeguards against potential data loss, ensuring your applications run smoothly and reliably.

Dgraph is an open-source, low-latency, high throughput native and distributed graph database. DGraph is designed to scale easily to meet the needs for small startups and large companies with huge amounts of data. It can handle terabytes structured data on commodity hardware with low latency to respond to user queries. It addresses business needs and can be used in cases that involve diverse social and knowledge networks, real-time recommendation engines and semantic search, pattern matching, fraud detection, serving relationship information, and serving web applications.

LedisDB is a fast NoSQL database system and library developed in Go. While it shares similarities with Redis, it distinguishes itself by storing data on disk. The library accommodates various data structures such as key-value pairs, lists, hashes, sorted sets, and sets. Additionally, LedisDB has evolved to support multiple backend databases, enhancing its versatility and usability for different applications. This makes it an appealing choice for developers seeking efficient data storage solutions.

LeanXcale is a rapidly scalable database that merges the features of both SQL and NoSQL systems. It is designed to handle large volumes of both batch and real-time data pipelines, ensuring that this data is accessible through SQL or GIS for diverse applications, including operational tasks, analytics, dashboard creation, or machine learning processes. Regardless of the technology stack in use, LeanXcale offers users the flexibility of SQL and NoSQL interfaces. The KiVi storage engine functions as a relational key-value data repository, enabling data access not only via the conventional SQL API but also through a direct ACID-compliant key-value interface. This particular interface facilitates high-speed data ingestion, optimizing efficiency by eliminating the overhead associated with SQL processing. Furthermore, its highly scalable and distributed storage engine spreads data across the cluster, thereby enhancing both performance and reliability while accommodating growing data needs seamlessly.

Tablestore facilitates effortless growth in data capacity and access concurrency through innovative technologies like data sharding and server load balancing, ensuring real-time access to vast amounts of structured data. It maintains three copies of data with strong consistency, ensuring high availability and reliability of services. Additionally, it supports both full and incremental data tunnels, allowing for smooth integration with a variety of products for big data analytics and real-time streaming computations. The distributed architecture boasts automatic scaling of single tables, accommodating data sizes up to 10 petabytes and handling access concurrency levels in the tens of millions. To further safeguard data, it incorporates multi-dimensional and multi-level security measures along with resource access management. With its low-latency performance, high concurrency capabilities, and elastic resources, paired with a Pay-As-You-Go pricing model, this service ensures that your risk control system operates under optimal conditions while providing strict oversight of transaction-related risks, ultimately enhancing operational efficiency. In essence, Tablestore combines cutting-edge technology with robust security to meet the demands of modern data management.

RocksDB is a high-performance database engine that employs a log-structured design and is entirely implemented in C++. It treats keys and values as byte streams of arbitrary sizes, allowing for flexibility in data representation. Specifically designed for rapid, low-latency storage solutions such as flash memory and high-speed disks, RocksDB capitalizes on the impressive read and write speeds provided by these technologies. The database supports a range of fundamental operations, from basic tasks like opening and closing a database to more complex functions such as merging and applying compaction filters. Its versatility makes RocksDB suitable for various workloads, including database storage engines like MyRocks as well as application data caching and embedded systems. This adaptability ensures that developers can rely on RocksDB for a wide spectrum of data management needs in different environments.

BangDB seamlessly incorporates AI, streaming capabilities, graph processing, and analytics directly within its database, empowering users to handle intricate data types like text, images, videos, and objects for immediate data processing and analysis. Users can ingest or stream various data types, process them, train models, make predictions, uncover patterns, and automate actions, facilitating applications such as IoT monitoring, fraud prevention, log analysis, lead generation, and personalized experiences. Modern applications necessitate the simultaneous ingestion, processing, and querying of diverse data types to address specific challenges effectively. BangDB accommodates a wide array of valuable data formats, simplifying problem-solving for users. The increasing demand for real-time data is driving the need for concurrent streaming and predictive analytics, which are essential for enhancing and optimizing business operations. As organizations continue to evolve, the ability to rapidly adapt to new data sources and insights will become increasingly vital for maintaining a competitive edge.

AllegroGraph represents a revolutionary advancement that facilitates limitless data integration through a proprietary methodology that merges all types of data and isolated knowledge into a cohesive Entity-Event Knowledge Graph, which is capable of handling extensive big data analytics. It employs distinctive federated sharding features that promote comprehensive insights and allow for intricate reasoning across a decentralized Knowledge Graph. Additionally, AllegroGraph offers an integrated version of Gruff, an innovative browser-based tool designed for visualizing graphs, helping users to explore and uncover relationships within their enterprise Knowledge Graphs. Furthermore, Franz's Knowledge Graph Solution encompasses both cutting-edge technology and expert services aimed at constructing robust Entity-Event Knowledge Graphs, leveraging top-tier tools, products, and extensive expertise to ensure optimal performance. This comprehensive approach not only enhances data utility but also empowers organizations to derive deeper insights and drive informed decision-making.

InterSystems IRIS, a cloud-first data platform, is a multi-model transactional database management engine, application development platform, interoperability engine and open analytics platform. InterSystems IRIS offers a variety of APIs that allow you to work with transactional persistent data simultaneously. These include key-value, relational and object, document, and multidimensional. Data can be managed by SQL, Java, node.js, .NET, C++, Python, and native server-side ObjectScript language. InterSystems IRIS features an Interoperability engine as well as modules for building AI solutions. InterSystems IRIS features horizontal scalability (sharding and ECP), and High Availability features such as Business intelligence, transaction support and backup.

In-Memory Computing Platform. Digital world is different. Microseconds are important. The world's most important organizations rely on us for powering their most sensitive applications at scale. If they meet the current requirement for immediate access, new data-enabled apps can transform your business. Hazelcast solutions can be used to complement any database and deliver results that are much faster than traditional systems of record. Hazelcast's distributed architecture ensures redundancy and continuous cluster up-time, as well as always available data to support the most demanding applications. The capacity grows with demand without compromising performance and availability. The cloud delivers the fastest in-memory data grid and third-generation high speed event processing.

Oracle NoSQL Database is specifically engineered to manage applications that demand high data throughput and quick response times, along with adaptable data structures. It accommodates various data types including JSON, tables, and key-value formats, and functions in both on-premises installations and cloud environments. The database is designed to scale dynamically in response to fluctuating workloads, offering distributed storage across multiple shards to guarantee both high availability and swift failover capabilities. With support for programming languages such as Python, Node.js, Java, C, and C#, as well as REST API drivers, it simplifies the development process for applications. Furthermore, it seamlessly integrates with other Oracle products like IoT, Golden Gate, and Fusion Middleware, enhancing its utility. The Oracle NoSQL Database Cloud Service is a completely managed solution, allowing developers to concentrate on creating applications without the burden of managing backend infrastructure. This service eliminates the complexities associated with infrastructure management, enabling teams to innovate and deploy solutions more efficiently.

Apache CouchDB™ provides seamless access to your data wherever you require it. The Couch Replication Protocol is utilized across a wide range of projects and products, accommodating diverse computing environments that include everything from globally distributed server clusters to mobile devices and web browsers. You can securely store your data on your own servers or with any major cloud service provider. Both web-based and native applications benefit from CouchDB's native JSON support and its capability to handle binary data efficiently for all storage requirements. The Couch Replication Protocol facilitates smooth data transfers between server clusters, mobile phones, and web browsers, delivering an impressive offline-first user experience while ensuring strong performance and reliability. Additionally, CouchDB features a developer-friendly query language and offers optional MapReduce functionality, enabling straightforward, efficient, and comprehensive data retrieval, making it an excellent choice for developers looking for flexibility and power in their data management solutions. This versatility in accessing and managing data makes CouchDB a valuable asset for modern application development.

MariaDB Platform is an enterprise-level open-source database solution. It supports transactional, analytical, and hybrid workloads, as well as relational and JSON data models. It can scale from standalone databases to data warehouses to fully distributed SQL, which can execute millions of transactions per second and perform interactive, ad-hoc analytics on billions upon billions of rows. MariaDB can be deployed on prem-on commodity hardware. It is also available on all major public cloud providers and MariaDB SkySQL, a fully managed cloud database. MariaDB.com provides more information.

Apache Druid is a distributed data storage solution that is open source. Its fundamental architecture merges concepts from data warehouses, time series databases, and search technologies to deliver a high-performance analytics database capable of handling a diverse array of applications. By integrating the essential features from these three types of systems, Druid optimizes its ingestion process, storage method, querying capabilities, and overall structure. Each column is stored and compressed separately, allowing the system to access only the relevant columns for a specific query, which enhances speed for scans, rankings, and groupings. Additionally, Druid constructs inverted indexes for string data to facilitate rapid searching and filtering. It also includes pre-built connectors for various platforms such as Apache Kafka, HDFS, and AWS S3, as well as stream processors and others. The system adeptly partitions data over time, making queries based on time significantly quicker than those in conventional databases. Users can easily scale resources by simply adding or removing servers, and Druid will manage the rebalancing automatically. Furthermore, its fault-tolerant design ensures resilience by effectively navigating around any server malfunctions that may occur. This combination of features makes Druid a robust choice for organizations seeking efficient and reliable real-time data analytics solutions.

JanusGraph stands out as a highly scalable graph database designed for efficiently storing and querying extensive graphs that can comprise hundreds of billions of vertices and edges, all managed across a cluster of multiple machines. This project, which operates under The Linux Foundation, boasts contributions from notable organizations such as Expero, Google, GRAKN.AI, Hortonworks, IBM, and Amazon. It offers both elastic and linear scalability to accommodate an expanding data set and user community. Key features include robust data distribution and replication methods to enhance performance and ensure fault tolerance. Additionally, JanusGraph supports multi-datacenter high availability and provides hot backups for data security. All these capabilities are available without any associated costs, eliminating the necessity for purchasing commercial licenses, as it is entirely open source and governed by the Apache 2 license. Furthermore, JanusGraph functions as a transactional database capable of handling thousands of simultaneous users performing complex graph traversals in real time. It ensures support for both ACID properties and eventual consistency, catering to various operational needs. Beyond online transactional processing (OLTP), JanusGraph also facilitates global graph analytics (OLAP) through its integration with Apache Spark, making it a versatile tool for data analysis and visualization. This combination of features makes JanusGraph a powerful choice for organizations looking to leverage graph data effectively.

QikkDB is a high-performance, GPU-accelerated columnar database designed to excel in complex polygon computations and large-scale data analytics. If you're managing billions of data points and require immediate insights, qikkDB is the solution you need. It is compatible with both Windows and Linux operating systems, ensuring flexibility for developers. The project employs Google Tests for its testing framework, featuring hundreds of unit tests alongside numerous integration tests to maintain robust quality. For those developing on Windows, it is advisable to use Microsoft Visual Studio 2019, with essential dependencies that include at least CUDA version 10.2, CMake 3.15 or a more recent version, vcpkg, and Boost libraries. Meanwhile, Linux developers will also require a minimum of CUDA version 10.2, CMake 3.15 or newer, and Boost for optimal operation. This software is distributed under the Apache License, Version 2.0, allowing for a wide range of usage. To simplify the installation process, users can opt for either an installation script or a Dockerfile to get qikkDB up and running seamlessly. Additionally, this versatility makes it an appealing choice for various development environments.

The enterprise database for time series, documents, and vectors. Store any type data and combine the simplicity and scalability NoSQL with SQL. CrateDB is a distributed database that runs queries in milliseconds regardless of the complexity, volume, and velocity.

KeyDB ensures complete compatibility with Redis modules, APIs, and protocols, allowing for a seamless integration that retains the functionality of your existing clients, scripts, and configurations. You can effortlessly switch to KeyDB while maintaining this compatibility. Its Multi-Master mode provides a single replicated dataset across multiple nodes, facilitating both read and write operations. Additionally, nodes can be replicated across different regions to achieve submillisecond latencies for local clients. With Cluster mode, the dataset can be divided across shards, enabling limitless read and write scalability while simultaneously supporting high availability through replica nodes. KeyDB also introduces new community-driven commands that enhance your ability to manipulate data. You can create your own commands and features using JavaScript via the ModJS module, which allows for the writing of functions in JavaScript that can be directly invoked by KeyDB. An example of a JavaScript function that could be loaded with this module is provided on the left, demonstrating how it can be called directly from your client, showcasing the flexibility and power of KeyDB. This capability not only enhances your data handling but also fosters a more dynamic interaction with your database environment.

QuerySurge is the smart Data Testing solution that automates the data validation and ETL testing of Big Data, Data Warehouses, Business Intelligence Reports and Enterprise Applications with full DevOps functionality for continuous testing. Use Cases - Data Warehouse & ETL Testing - Big Data (Hadoop & NoSQL) Testing - DevOps for Data / Continuous Testing - Data Migration Testing - BI Report Testing - Enterprise Application/ERP Testing Features Supported Technologies - 200+ data stores are supported QuerySurge Projects - multi-project support Data Analytics Dashboard - provides insight into your data Query Wizard - no programming required Design Library - take total control of your custom test desig BI Tester - automated business report testing Scheduling - run now, periodically or at a set time Run Dashboard - analyze test runs in real-time Reports - 100s of reports API - full RESTful API DevOps for Data - integrates into your CI/CD pipeline Test Management Integration QuerySurge will help you: - Continuously detect data issues in the delivery pipeline - Dramatically increase data validation coverage - Leverage analytics to optimize your critical data - Improve your data quality at speed

Apache Trafodion serves as a webscale SQL-on-Hadoop solution that facilitates transactional or operational processes within the Apache Hadoop ecosystem. By leveraging the inherent scalability, elasticity, and flexibility of Hadoop, Trafodion enhances its capabilities to ensure transactional integrity, which opens the door for a new wave of big data applications to operate seamlessly on Hadoop. The platform supports the full ANSI SQL language, allowing for JDBC/ODBC connectivity suitable for both Linux and Windows clients. It provides distributed ACID transaction protection that spans multiple statements, tables, and rows, all while delivering performance enhancements specifically designed for OLTP workloads through both compile-time and run-time optimizations. Trafodion is also equipped with a parallel-aware query optimizer that efficiently handles large datasets, enabling developers to utilize their existing SQL knowledge and boost productivity. Furthermore, its distributed ACID transactions maintain data consistency across various rows and tables, making it interoperable with a wide range of existing tools and applications. This solution is neutral to both Hadoop and Linux distributions, providing a straightforward integration path into any existing Hadoop infrastructure. Thus, Apache Trafodion not only enhances the power of Hadoop but also simplifies the development process for users.

Amazon Neptune is an efficient and dependable graph database service that is fully managed, facilitating the development and operation of applications that handle intricate, interconnected datasets. At its heart, Amazon Neptune features a specialized, high-performance database engine tailored for the storage of billions of relationships while enabling rapid querying with latency measured in milliseconds. It accommodates widely-used graph models, including Property Graph and W3C's RDF, along with their associated query languages, Apache TinkerPop Gremlin and SPARQL, which simplifies the process of crafting queries for navigating complex datasets. This service supports various graph-based applications, including recommendation systems, fraud detection mechanisms, knowledge graphs, drug discovery initiatives, and enhanced network security protocols. With a proactive approach, it enables the detection and analysis of IT infrastructure threats through a multi-layered security framework. Furthermore, it allows users to visualize their entire infrastructure to effectively plan, forecast, and address potential risks, while also enabling the creation of graph queries for the near-real-time identification of fraudulent patterns in financial and purchasing activities, thereby enhancing overall security and efficiency.

Luna offers a subscription service for Apache Cassandra support and expertise through DataStax, allowing users to take advantage of open-source Cassandra while benefiting from the knowledge and experience of the team that created most of its code and has supported some of the largest deployments globally. With Luna, you gain access to best practices, expert advice, and SLA-based support to ensure your Cassandra setup remains optimal. You can scale your operations without sacrificing performance or latency, effectively managing even the most demanding real-time workloads with ease. The service empowers you to create dynamic and highly-interactive customer experiences with exceptionally fast read and write capabilities. Additionally, Luna helps resolve issues and adhere to best practices in managing Cassandra clusters. The support provided encompasses the entire application life cycle, facilitating a deeper collaboration with your team throughout the implementation process, ensuring that your needs are met at every stage. Ultimately, Luna enhances your ability to harness the full potential of Cassandra for your business objectives.

Enhance performance by utilizing a scalable, secure, and highly available in-memory service tailored for Redis and Memcached. Memorystore simplifies complex procedures associated with open source Redis and Memcached, such as ensuring high availability, managing failover, conducting patching, and monitoring, allowing developers to focus more on coding. You can begin with the most basic tier and smallest configuration, gradually expanding your instance with minimal disruption. Memorystore for Memcached has the capacity to manage clusters up to 5 TB, delivering millions of queries per second at remarkably low latency. In contrast, Memorystore for Redis instances are designed to be replicated across two zones, offering a service level agreement of 99.9% availability. Continuous monitoring and automatic failover mechanisms ensure that applications face minimal interruptions. You can select from two of the most widely used open source caching solutions to develop your applications. Memorystore provides full protocol compatibility for both Redis and Memcached, enabling you to choose the caching engine that best aligns with your budget and availability needs while maximizing your application's performance. By leveraging these features, developers can significantly improve their operational efficiency.

OrbitDB functions as a decentralized, serverless, peer-to-peer database that leverages IPFS for data storage and utilizes Libp2p Pubsub for seamless synchronization among peers. It incorporates Merkle-CRDTs to facilitate conflict-free writing and merging of database entries, making it ideal for decentralized applications, blockchain projects, and web apps designed to operate primarily offline. The platform provides a range of database types that cater to distinct requirements: 'events' serves as immutable append-only logs, 'documents' allows for JSON document storage indexed by specific keys, 'keyvalue' offers conventional key-value pair storage, and 'keyvalue-indexed' provides LevelDB-indexed key-value data. Each of these database types is constructed on OpLog, a structure that is immutable, cryptographically verifiable, and based on operation-driven CRDT principles. The JavaScript implementation is compatible with both browser and Node.js environments, while a version in Go is actively maintained by the Berty project, ensuring a wide range of support for developers. This flexibility and adaptability make OrbitDB a powerful choice for those looking to implement modern data solutions in distributed systems.

HerdDB is a distributed SQL database developed in Java, making it embeddable within any Java Virtual Machine. It has been specifically optimized for rapid write operations and efficient access patterns for primary key read and updates. Capable of managing numerous tables, HerdDB allows for straightforward addition and removal of hosts as well as flexible reconfiguration of tablespaces to effectively balance loads across multiple systems. Utilizing Apache Zookeeper and Apache Bookkeeper, HerdDB achieves a fully replicated architecture that eliminates any single point of failure. At its core, HerdDB shares similarities with key-value NoSQL databases, but it also incorporates an SQL abstraction layer along with JDBC Driver support, allowing users to easily transition existing applications to its platform. Additionally, at Diennea, we have created EmailSuccess, a highly efficient Mail Transfer Agent designed to deliver millions of emails per hour to recipients worldwide, showcasing the capabilities of our technology. This seamless integration of advanced database management and email delivery systems reflects our commitment to providing powerful solutions for modern data handling.