Alternatives to InfluxDB

Google Cloud is an online service that lets you create everything from simple websites to complex apps for businesses of any size. Customers who are new to the system will receive $300 in credits for testing, deploying, and running workloads. Customers can use up to 25+ products free of charge. Use Google's core data analytics and machine learning. All enterprises can use it. It is secure and fully featured. Use big data to build better products and find answers faster. You can grow from prototypes to production and even to planet-scale without worrying about reliability, capacity or performance. Virtual machines with proven performance/price advantages, to a fully-managed app development platform. High performance, scalable, resilient object storage and databases. Google's private fibre network offers the latest software-defined networking solutions. Fully managed data warehousing and data exploration, Hadoop/Spark and messaging.

Cloud-based solution for observability that helps businesses manage and track workload and performance through a single dashboard. Monitor all the services you run on your cloud without compromising cost, granularity or scale. Groundcover is a cloud-native APM solution that makes observability easy so you can focus on creating world-class products. Groundcover's proprietary sensor unlocks unprecedented granularity for all your applications. This eliminates the need for costly changes in code and development cycles, ensuring monitoring continuity.

StarTree Cloud is a fully-managed real-time analytics platform designed for OLAP at massive speed and scale for user-facing applications. Powered by Apache Pinot, StarTree Cloud provides enterprise-grade reliability and advanced capabilities such as tiered storage, scalable upserts, plus additional indexes and connectors. It integrates seamlessly with transactional databases and event streaming platforms, ingesting data at millions of events per second and indexing it for lightning-fast query responses. StarTree Cloud is available on your favorite public cloud or for private SaaS deployment. StarTree Cloud includes StarTree Data Manager, which allows you to ingest data from both real-time sources such as Amazon Kinesis, Apache Kafka, Apache Pulsar, or Redpanda, as well as batch data sources such as data warehouses like Snowflake, Delta Lake or Google BigQuery, or object stores like Amazon S3, Apache Flink, Apache Hadoop, or Apache Spark. StarTree ThirdEye is an add-on anomaly detection system running on top of StarTree Cloud that observes your business-critical metrics, alerting you and allowing you to perform root-cause analysis — all in real-time.

Ninox empowers you to store and organize complex data with ease and structure. Its highly customizable user interface lets you process, analyze, and evaluate data of any kind. Plus, with Ninox's API, you can seamlessly integrate services like Google for even greater flexibility. Accessible on all platforms, Ninox works effortlessly through native macOS, iOS, and Android apps or any web browser. Create custom apps tailored to your needs using built-in templates, drag-and-drop formulas, and scripting. The visual editor makes it simple to design triggers, fields, custom forms, and more. Ninox also ensures real-time syncing across devices, enabling smooth transitions and uninterrupted workflows.

RaimaDB, an embedded time series database that can be used for Edge and IoT devices, can run in-memory. It is a lightweight, secure, and extremely powerful RDBMS. It has been field tested by more than 20 000 developers around the world and has been deployed in excess of 25 000 000 times. RaimaDB is a high-performance, cross-platform embedded database optimized for mission-critical applications in industries such as IoT and edge computing. Its lightweight design makes it ideal for resource-constrained environments, supporting both in-memory and persistent storage options. RaimaDB offers flexible data modeling, including traditional relational models and direct relationships through network model sets. With ACID-compliant transactions and advanced indexing methods like B+Tree, Hash Table, R-Tree, and AVL-Tree, it ensures data reliability and efficiency. Built for real-time processing, it incorporates multi-version concurrency control (MVCC) and snapshot isolation, making it a robust solution for applications demanding speed and reliability.

Epsagon allows teams to instantly visualize, understand, and optimize their microservice architectures. With our unique lightweight auto-instrumentation, gaps in data and manual work associated with other APM solutions are eliminated, providing significant reductions in issue detection, root cause analysis and resolution times. Epsagon can increase development speed and reduce application downtime.

ScaleGrid is a fully managed Database-as-a-Service (DBaaS) platform that helps you automate your time-consuming database administration tasks both in the cloud and on-premises. ScaleGrid makes it easy to provision, monitor, backup, and scale open-source databases. It offers advanced security, high availability, query analysis, and troubleshooting support to improve your deployments' performance. The following databases are supported: - MySQL - PostgreSQL - Redis™. - MongoDB®, database - Greenplum™ (coming soon) ScaleGrid supports both public and privately-owned clouds such as AWS, Azure and Google Cloud Platform (GCP), DigitalOcean and Linode, Oracle Cloud Infrastructure, (OCI), VMware, and OpenStack. ScaleGrid is used by thousands of developers, startups, as well as enterprise customers such as Accenture, Meteor and Atlassian. It handles all your database operations at any scale, so you can concentrate on your application performance.

The easiest cloud platform for developers and teams. DigitalOcean makes it easy to deploy, manage, and scale cloud apps faster and more efficiently. DigitalOcean makes it easy to manage infrastructure for businesses and teams, no matter how many virtual machines you have. DigitalOcean App Platform: Create, deploy, scale and scale apps quickly with a fully managed solution. We will manage the infrastructure, dependencies, and app runtimes so you can quickly push code to production. You can quickly build, deploy, manage, scale, and scale apps using a simple, intuitive, visually rich experience. Apps are automatically secured We manage, renew, and create SSL certificates for you. We also protect your apps against DDoS attacks. We help you focus on the important things: creating amazing apps. We can manage infrastructure, databases, operating systems, applications, runtimes, and other dependencies.

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.

Amazon Relational Database Service (Amazon RDS) simplifies the process of establishing, managing, and scaling a relational database in the cloud. It offers a cost-effective and adjustable capacity while taking care of tedious administrative tasks such as hardware provisioning, setting up databases, applying patches, and performing backups. This allows you to concentrate on your applications, ensuring they achieve fast performance, high availability, security, and compatibility. Amazon RDS supports various database instance types optimized for memory, performance, or I/O, and offers a selection of six well-known database engines, including Amazon Aurora, PostgreSQL, MySQL, MariaDB, Oracle Database, and SQL Server. Additionally, the AWS Database Migration Service facilitates the seamless migration or replication of your existing databases to Amazon RDS, making the transition straightforward and efficient. Overall, Amazon RDS empowers businesses to leverage robust database solutions without the burden of complex management tasks.

Amazon ElastiCache enables users to effortlessly establish, operate, and expand widely-used open-source compatible in-memory data stores in the cloud environment. It empowers the development of data-driven applications or enhances the efficiency of existing databases by allowing quick access to data through high throughput and minimal latency in-memory stores. This service is particularly favored for various real-time applications such as caching, session management, gaming, geospatial services, real-time analytics, and queuing. With fully managed options for Redis and Memcached, Amazon ElastiCache caters to demanding applications that necessitate response times in the sub-millisecond range. Functioning as both an in-memory data store and a cache, it is designed to meet the needs of applications that require rapid data retrieval. Furthermore, by utilizing a fully optimized architecture that operates on dedicated nodes for each customer, Amazon ElastiCache guarantees incredibly fast and secure performance for its users' critical workloads. This makes it an essential tool for businesses looking to enhance their application's responsiveness and scalability.

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.

Amazon Timestream is an efficient, scalable, and serverless time series database designed for IoT and operational applications, capable of storing and analyzing trillions of events daily with speeds up to 1,000 times faster and costs as low as 1/10th that of traditional relational databases. By efficiently managing the lifecycle of time series data, Amazon Timestream reduces both time and expenses by keeping current data in memory while systematically transferring historical data to a more cost-effective storage tier based on user-defined policies. Its specialized query engine allows users to seamlessly access and analyze both recent and historical data without the need to specify whether the data is in memory or in the cost-optimized tier. Additionally, Amazon Timestream features integrated time series analytics functions, enabling users to detect trends and patterns in their data almost in real-time, making it an invaluable tool for data-driven decision-making. Furthermore, this service is designed to scale effortlessly with your data needs while ensuring optimal performance and cost efficiency.

QuasarDB, the core of Quasar's intelligence, is an advanced, distributed, column-oriented database management system specifically engineered for high-performance timeseries data handling, enabling real-time processing for massive petascale applications. It boasts up to 20 times less disk space requirement, making it exceptionally efficient. The unmatched ingestion and compression features of QuasarDB allow for up to 10,000 times quicker feature extraction. This database can perform real-time feature extraction directly from raw data via an integrated map/reduce query engine, a sophisticated aggregation engine that utilizes SIMD capabilities of contemporary CPUs, and stochastic indexes that consume minimal disk storage. Its ultra-efficient resource utilization, ability to integrate with object storage solutions like S3, innovative compression methods, and reasonable pricing structure make it the most economical timeseries solution available. Furthermore, QuasarDB is versatile enough to operate seamlessly across various platforms, from 32-bit ARM devices to high-performance Intel servers, accommodating both Edge Computing environments and traditional cloud or on-premises deployments. Its scalability and efficiency make it an ideal choice for businesses aiming to harness the full potential of their data in real-time.

A Time Series Database (TSDB) is designed for rapid data input and output, allowing for swift reading and writing of information. It achieves impressive compression rates that lead to economical data storage solutions. Moreover, this service facilitates visualization techniques, such as precision reduction, interpolation, and multi-metric aggregation, alongside the processing of query results. By utilizing TSDB, businesses can significantly lower their storage expenses while enhancing the speed of data writing, querying, and analysis. This capability allows for the management of vast quantities of data points and enables more frequent data collection. Its applications span various sectors, including IoT monitoring, enterprise energy management systems (EMSs), production security oversight, and power supply monitoring. Additionally, TSDB is instrumental in optimizing database structures and algorithms, capable of processing millions of data points in mere seconds. By employing an advanced compression method, it can minimize each data point's size to just 2 bytes, leading to over 90% savings in storage costs. Consequently, this efficiency not only benefits businesses financially but also streamlines operational workflows across different industries.

GridDB utilizes multicast communication to form its cluster, so it's essential to configure the network for this purpose. Start by verifying the host name and IP address; you can do this by running the command “hostname -i” to check the host's IP address configuration. If the reported IP address matches the specified value below, you can proceed directly to the next section without any further network adjustments. GridDB is a database designed to manage a collection of data entries, each consisting of a key paired with several values. In addition to functioning as an in-memory database that organizes all data within the memory, it also supports a hybrid architecture that combines both memory and disk storage, which can include solid-state drives (SSDs). This flexibility allows for efficient data management and retrieval, catering to various application needs.

QuestDB is an advanced relational database that focuses on column-oriented storage optimized for time series and event-driven data. It incorporates SQL with additional features tailored for time-based analytics to facilitate real-time data processing. This documentation encompasses essential aspects of QuestDB, including initial setup instructions, comprehensive usage manuals, and reference materials for syntax, APIs, and configuration settings. Furthermore, it elaborates on the underlying architecture of QuestDB, outlining its methods for storing and querying data, while also highlighting unique functionalities and advantages offered by the platform. A key feature is the designated timestamp, which empowers time-focused queries and efficient data partitioning. Additionally, the symbol type enhances the efficiency of managing and retrieving frequently used strings. The storage model explains how QuestDB organizes records and partitions within its tables, and the use of indexes can significantly accelerate read access for specific columns. Moreover, partitions provide substantial performance improvements for both calculations and queries. With its SQL extensions, users can achieve high-performance time series analysis using a streamlined syntax that simplifies complex operations. Overall, QuestDB stands out as a powerful tool for handling time-oriented data effectively.

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.

OpenTSDB comprises a Time Series Daemon (TSD) along with a suite of command line tools. Users primarily engage with OpenTSDB by operating one or more independent TSDs, as there is no centralized master or shared state, allowing for the scalability to run multiple TSDs as necessary to meet varying loads. Each TSD utilizes HBase, an open-source database, or the hosted Google Bigtable service for the storage and retrieval of time-series data. The schema designed for the data is highly efficient, enabling rapid aggregations of similar time series while minimizing storage requirements. Users interact with the TSD without needing direct access to the underlying storage system. Communication with the TSD can be accomplished through a straightforward telnet-style protocol, an HTTP API, or a user-friendly built-in graphical interface. To begin utilizing OpenTSDB, the initial task is to send time series data to the TSDs, and there are various tools available to facilitate the import of data from different sources into OpenTSDB. Overall, OpenTSDB's design emphasizes flexibility and efficiency for time series data management.

TimescaleDB is the most popular open-source relational database that supports time-series data. Fully managed or self-hosted. You can rely on the same PostgreSQL that you love. It has full SQL, rock-solid reliability and a huge ecosystem. Write millions of data points per node. Horizontally scale up to petabytes. Don't worry too much about cardinality. Reduce complexity, ask more questions and build more powerful applications. You will save money with 94-97% compression rates using best-in-class algorithms, and other performance improvements. Modern cloud-native relational database platform that stores time-series data. It is based on PostgreSQL and TimescaleDB. This is the fastest, easiest, and most reliable way to store all of your time-series information. All observability data can be considered time-series data. Time-series problems are those that require efficient solutions to infrastructure and application problems.

SiriDB is optimized for speed. Inserts and queries are answered quickly. You can speed up your development with the custom query language. SiriDB is flexible and can be scaled on the fly. There is no downtime when you update or expand your database. You can scale your database without losing speed. As we distribute your time series data across all pools, we make full use of all resources. SiriDB was designed to deliver unmatched performance with minimal downtime. A SiriDB cluster distributes time series across multiple pools. Each pool has active replicas that can be used for load balancing or redundancy. The database can still be accessed even if one of the replicas is unavailable.

Warp 10 is a modular open source platform that collects, stores, and allows you to analyze time series and sensor data. Shaped for the IoT with a flexible data model, Warp 10 provides a unique and powerful framework to simplify your processes from data collection to analysis and visualization, with the support of geolocated data in its core model (called Geo Time Series). Warp 10 offers both a time series database and a powerful analysis environment, which can be used together or independently. It will allow you to make: statistics, extraction of characteristics for training models, filtering and cleaning of data, detection of patterns and anomalies, synchronization or even forecasts. The Platform is GDPR compliant and secure by design using cryptographic tokens to manage authentication and authorization. The Analytics Engine can be implemented within a large number of existing tools and ecosystems such as Spark, Kafka Streams, Hadoop, Jupyter, Zeppelin and many more. From small devices to distributed clusters, Warp 10 fits your needs at any scale, and can be used in many verticals: industry, transportation, health, monitoring, finance, energy, etc.

VictoriaMetrics is a cost-effective, scalable monitoring solution that can also be used as a time series database. It can also be used to store Prometheus' long-term data. VictoriaMetrics is a single executable that does not have any external dependencies. All configuration is done using explicit command-line flags and reasonable defaults. It provides global query view. Multiple Prometheus instances, or other data sources, may insert data into VictoriaMetrics. Later this data may be queried via a single query. It can handle high cardinality and high churn rates issues by using a series limiter.

Fauna is a data API that supports rich clients with serverless backends. It provides a web-native interface that supports GraphQL, custom business logic, frictionless integration to the serverless ecosystem, and a multi-cloud architecture that you can trust and grow with.

VPVision is a complete energy monitoring solution that monitors all utilities in your company. VPVision software allows you to see the true cost of all utilities and make informed decisions about your investments and costs. You can access your data from anywhere with the latest web technology. You can add channels, customize dashboards and create your own reports to analyze your savings and make them transparent. VPVision is your guide to energy savings. VPVision makes energy saving simple, quick, and rewarding. It makes it possible to view data from anywhere using the latest web technology. VPVision analyzes flow data to reveal your savings potential. VPVision allows you to see all utility costs, including steam, compressed air, technical gas, steam, natural gas and electricity, as well as wastewater, heating fuels and heating fuels. VPVision is flexible and adaptable and can be used by small and large companies as well as those in growth.

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.

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.

Optimize your time and reduce expenses by simplifying data pipelines using hassle-free open source solutions. Covering everything from data ingestion to visualization, all components are seamlessly integrated, fully managed, and exceptionally reliable, ensuring your engineering team enjoys working with data. You can opt for any of DoubleCloud’s managed open source services or take advantage of the entire platform's capabilities, which include data storage, orchestration, ELT, and instantaneous visualization. We offer premier open source services such as ClickHouse, Kafka, and Airflow, deployable on platforms like Amazon Web Services or Google Cloud. Our no-code ELT tool enables real-time data synchronization between various systems, providing a fast, serverless solution that integrates effortlessly with your existing setup. With our managed open-source data visualization tools, you can easily create real-time visual representations of your data through interactive charts and dashboards. Ultimately, our platform is crafted to enhance the daily operations of engineers, making their tasks more efficient and enjoyable. This focus on convenience is what sets us apart in the industry.

Enhance your metrics and alerting capabilities using a top-tier open-source monitoring tool. Prometheus inherently organizes all data as time series, which consist of sequences of timestamped values associated with the same metric and a specific set of labeled dimensions. In addition to the stored time series, Prometheus has the capability to create temporary derived time series based on query outcomes. The tool features a powerful query language known as PromQL (Prometheus Query Language), allowing users to select and aggregate time series data in real time. The output from an expression can be displayed as a graph, viewed in tabular format through Prometheus’s expression browser, or accessed by external systems through the HTTP API. Configuration of Prometheus is achieved through a combination of command-line flags and a configuration file, where the flags are used to set immutable system parameters like storage locations and retention limits for both disk and memory. This dual method of configuration ensures a flexible and tailored monitoring setup that can adapt to various user needs. For those interested in exploring this robust tool, further details can be found at: https://ancillary-proxy.atarimworker.io?url=https%3A%2F%2Fsourceforge.net%2Fprojects%2Fprometheus.mirror%2F

IBM Informix® is a highly adaptable and efficient database that can effortlessly combine SQL, NoSQL/JSON, as well as time series and spatial data. Its flexibility and user-friendly design position Informix as a top choice for diverse settings, ranging from large-scale enterprise data warehouses to smaller individual application development projects. Moreover, due to its compact footprint and self-managing features, Informix is particularly advantageous for embedded data management applications. The rising demand for IoT data processing necessitates strong integration and processing capabilities, which Informix fulfills with its hybrid database architecture that requires minimal administrative effort and has a small memory footprint while delivering robust functionality. Notably, Informix is well-equipped for multi-tiered architectures that necessitate processing at various levels, including devices, gateway layers, and cloud environments. Furthermore, it incorporates native encryption to safeguard data both at rest and in transit. Additionally, Informix supports a flexible schema alongside multiple APIs and configurations, making it a versatile choice for modern data management challenges.

Real-time analytics on raw data. Live ingest from S3, DynamoDB, DynamoDB and more. Raw data can be accessed as SQL tables. In minutes, you can create amazing data-driven apps and live dashboards. Rockset is a serverless analytics and search engine that powers real-time applications and live dashboards. You can directly work with raw data such as JSON, XML and CSV. Rockset can import data from real-time streams and data lakes, data warehouses, and databases. You can import real-time data without the need to build pipelines. Rockset syncs all new data as it arrives in your data sources, without the need to create a fixed schema. You can use familiar SQL, including filters, joins, and aggregations. Rockset automatically indexes every field in your data, making it lightning fast. Fast queries are used to power your apps, microservices and live dashboards. Scale without worrying too much about servers, shards or pagers.

Materialize is an innovative reactive database designed to provide updates to views incrementally. It empowers developers to seamlessly work with streaming data through the use of standard SQL. One of the key advantages of Materialize is its ability to connect directly to a variety of external data sources without the need for pre-processing. Users can link to real-time streaming sources such as Kafka, Postgres databases, and change data capture (CDC), as well as access historical data from files or S3. The platform enables users to execute queries, perform joins, and transform various data sources using standard SQL, presenting the outcomes as incrementally-updated Materialized views. As new data is ingested, queries remain active and are continuously refreshed, allowing developers to create data visualizations or real-time applications with ease. Moreover, constructing applications that utilize streaming data becomes a straightforward task, often requiring just a few lines of SQL code, which significantly enhances productivity. With Materialize, developers can focus on building innovative solutions rather than getting bogged down in complex data management tasks.

Instaclustr, the Open Source-as a Service company, delivers reliability at scale. We provide database, search, messaging, and analytics in an automated, trusted, and proven managed environment. We help companies focus their internal development and operational resources on creating cutting-edge customer-facing applications. Instaclustr is a cloud provider that works with AWS, Heroku Azure, IBM Cloud Platform, Azure, IBM Cloud and Google Cloud Platform. The company is certified by SOC 2 and offers 24/7 customer support.

Imply is a cutting-edge analytics platform that leverages Apache Druid to manage extensive, high-performance OLAP (Online Analytical Processing) tasks in real-time. It excels at ingesting data instantly, delivering rapid query results, and enabling intricate analytical inquiries across vast datasets while maintaining low latency. This platform is specifically designed for enterprises that require engaging analytics, real-time dashboards, and data-centric decision-making on a large scale. Users benefit from an intuitive interface for exploring data, enhanced by features like multi-tenancy, detailed access controls, and operational insights. Its distributed architecture and ability to scale make Imply particularly advantageous for applications in streaming data analysis, business intelligence, and real-time monitoring across various sectors. Furthermore, its capabilities ensure that organizations can efficiently adapt to increasing data demands and quickly derive actionable insights from their data.

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.

Machbase is a leading time-series database designed for real-time storage and analysis of vast amounts of sensor data from various facilities. It stands out as the only database management system (DBMS) capable of processing and analyzing large datasets at remarkable speeds, showcasing its impressive capabilities. Experience the extraordinary processing speeds that Machbase offers! This innovative product allows for immediate handling, storage, and analysis of sensor information. It achieves rapid storage and querying of sensor data by integrating the DBMS directly into Edge devices. Additionally, it provides exceptional performance in data storage and extraction when operating on a single server. With the ability to configure multi-node clusters, Machbase offers enhanced availability and scalability. Furthermore, it serves as a comprehensive management solution for Edge computing, addressing device management, connectivity, and data handling needs effectively. In a fast-paced data-driven world, Machbase proves to be an essential tool for industries relying on real-time sensor data analysis.

Convex is a reactive backend platform that is open-source and allows developers to create full-stack applications solely using TypeScript. This platform features a document-relational database that employs TypeScript for writing queries and mutations, thereby promoting type safety and fostering smooth integration with frontend components. With Convex, real-time synchronization is automatically managed between the frontend, backend, and database states, removing the need for developers to handle state management, cache invalidation, or WebSockets manually. Additionally, it provides in-built functionalities such as cloud functions, scheduling, authentication, file storage, and an array of components that can be easily integrated using a simple npm install command. Developers have the capability to define their entire backend through code, encompassing database schemas, queries, and APIs, all of which benefit from type-checking and autocompletion, while AI can assist in generating code with remarkable precision. The architecture of Convex guarantees that all transactions are serializable, ensuring strong consistency and effectively eliminating race conditions. Overall, this platform simplifies backend development while enhancing developer productivity through its comprehensive TypeScript support.

The ITTIA DB suite brings together advanced features for time series, real-time data streaming, and analytics tailored for embedded systems, ultimately streamlining development processes while minimizing expenses. With ITTIA DB IoT, users can access a compact embedded database designed for real-time operations on resource-limited 32-bit microcontrollers (MCUs), while ITTIA DB SQL serves as a robust time-series embedded database that operates efficiently on both single and multicore microprocessors (MPUs). These ITTIA DB offerings empower devices to effectively monitor, process, and retain real-time data. Additionally, the products are specifically engineered to meet the needs of Electronic Control Units (ECUs) within the automotive sector. To ensure data security, ITTIA DB incorporates comprehensive protection mechanisms against unauthorized access, leveraging encryption, authentication, and the DB SEAL feature. Furthermore, ITTIA SDL adheres to the standards set forth by IEC/ISO 62443, reinforcing its commitment to safety. By integrating ITTIA DB, developers can seamlessly collect, process, and enhance incoming real-time data streams through a specialized SDK designed for edge devices, allowing for efficient searching, filtering, joining, and aggregating of data right at the edge. This comprehensive approach not only optimizes performance but also supports the growing demand for real-time data handling in today's technology landscape.

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.

Oracle's database offerings provide clients with cost-effective and high-efficiency options, including the renowned multi-model database management system, as well as in-memory, NoSQL, and MySQL databases. The Oracle Autonomous Database, which can be accessed on-premises through Oracle Cloud@Customer or within the Oracle Cloud Infrastructure, allows users to streamline their relational database systems and lessen management burdens. By removing the intricacies associated with operating and securing Oracle Database, Oracle Autonomous Database ensures customers experience exceptional performance, scalability, and reliability. Furthermore, organizations concerned about data residency and network latency can opt for on-premises deployment of Oracle Database. Additionally, clients who rely on specific versions of Oracle databases maintain full authority over their operational versions and the timing of any updates. This flexibility empowers businesses to tailor their database environments according to their unique requirements.

KairosDB allows data ingestion through various protocols including Telnet, Rest, and Graphite, in addition to supporting plugins for further flexibility. It utilizes Cassandra, a well-regarded NoSQL database, to manage time series data effectively. The database schema is organized into three column families, facilitating efficient data storage. The API offers a range of functionalities, such as listing existing metric names, retrieving tag names and their corresponding values, storing metric data points, and querying these points for analysis. Upon a standard installation, users can access a query page that enables them to extract data from the database easily. This tool is primarily tailored for development applications. Aggregators within the system can perform operations on data points, allowing for down sampling and analysis. A set of standard functions, including min, max, sum, count, and mean, among others, are readily available for users to utilize. Additionally, the KairosDB server supports import and export functionalities via the command line interface. Internal metrics related to the database not only provide insights into the stored data but also allow for monitoring the performance of the server itself, ensuring optimal operation and efficiency. This comprehensive approach makes KairosDB a powerful solution for managing time series data.

SAP HANA is an in-memory database designed to handle both transactional and analytical workloads using a single copy of data, regardless of type. It effectively dissolves the barriers between transactional and analytical processes within organizations, facilitating rapid decision-making whether deployed on-premises or in the cloud. This innovative database management system empowers users to create intelligent, real-time solutions, enabling swift decision-making from a unified data source. By incorporating advanced analytics, it enhances the capabilities of next-generation transaction processing. Organizations can build data solutions that capitalize on cloud-native attributes such as scalability, speed, and performance. With SAP HANA Cloud, businesses can access reliable, actionable information from one cohesive platform while ensuring robust security, privacy, and data anonymization, reflecting proven enterprise standards. In today's fast-paced environment, an intelligent enterprise relies on timely insights derived from data, emphasizing the need for real-time delivery of such valuable information. As the demand for immediate access to insights grows, leveraging an efficient database like SAP HANA becomes increasingly critical for organizations aiming to stay competitive.

Introducing a premier high-performance distributed SQL database that is open source and designed specifically for cloud-native environments, ideal for powering applications on a global internet scale. Experience minimal latency, often in the single-digit milliseconds, allowing you to create incredibly fast cloud applications by executing queries directly from the database itself. Handle immense workloads effortlessly, achieving millions of transactions per second and accommodating several terabytes of data on each node. With geo-distribution capabilities, you can deploy your database across various regions and cloud platforms, utilizing synchronous or multi-master replication for optimal performance. Tailored for modern cloud-native architectures, YugabyteDB accelerates the development, deployment, and management of applications like never before. Enjoy enhanced developer agility by tapping into the full capabilities of PostgreSQL-compatible SQL alongside distributed ACID transactions. Maintain resilient services with assured continuous availability, even amidst failures in compute, storage, or network infrastructure. Scale your resources on demand, easily adding or removing nodes as needed, and eliminate the necessity for over-provisioned clusters. Additionally, benefit from significantly reduced user latency, ensuring a seamless experience for your app users.

Designed specifically for optimizing compute, memory, and storage, Oxla serves as a self-hosted data warehouse that excels in handling large-scale, low-latency analytics while providing strong support for time-series data. While cloud data warehouses may suit many, they are not universally applicable; as operations expand, the ongoing costs of cloud computing can surpass initial savings on infrastructure, particularly in regulated sectors that demand comprehensive data control beyond mere VPC and BYOC setups. Oxla surpasses both traditional and cloud-based warehouses by maximizing efficiency, allowing for the scalability of expanding datasets with predictable expenses, whether on-premises or in various cloud environments. Deployment, execution, and maintenance of Oxla can be easily managed using Docker and YAML, enabling a range of workloads to thrive within a singular, self-hosted data warehouse. In this way, Oxla provides a tailored solution for organizations seeking both efficiency and control in their data management strategies.

Experience a fully managed and hosted PostgreSQL solution that delivers exceptional performance along with all the necessary extensions readily available. You can establish your fully managed PostgreSQL instance in under ten minutes, using our web console or through various programming methods such as API, CLI, Terraform provider, or Kubernetes operator. Our standby nodes automatically serve as read replicas, and you have the flexibility to generate additional read replicas across different public clouds and geographic regions, enabling the creation of multi-cloud architectures. With Point-In-Time Recovery, you can restore your data to any moment within your chosen retention timeframe. This fully managed SQL relational database is deployable in the cloud environment of your preference, offering a reputation for reliability, a comprehensive feature set, and outstanding performance. It is suitable for a wide range of applications, including location-based services, critical business solutions, or serving as a general transactional database to meet diverse needs. As a result, it serves as an excellent choice for organizations looking to enhance their data management capabilities effectively.