Alternatives to PipelineDB

Cloud SQL is a fully managed relational database service that supports MySQL, PostgreSQL, and SQL Server. It includes rich extensions, configuration flags, and developer ecosystems. Cloud SQL offers $300 in credits for new customers. You won't pay until you upgrade. Reduce maintenance costs by using fully managed MySQL, PostgreSQL, and SQL Server databases. The SRE team provides 24/7 support for reliable and secure services. Data encryption in transit and at rest ensures the highest level of security. Private connectivity with Virtual Private Cloud, user-controlled network access, and firewall protection add an additional layer of safety. Compliant with SSAE 16, ISO 27001, PCI DSS, and HIPAA, you can trust your data to be protected. Scale your database instances with a single API request, whether you are just testing or need a highly available database in production. Standard connection drivers and integrated migration tools let you create and connect to a database in a matter of minutes. Transform your database management with AI-driven support in Gemini, currently available in preview on Cloud SQL. It enhances development, optimizes performance, and simplifies fleet management, governance, and migration.

DbVisualizer is one of the world’s most popular database clients. Developers, analysts, and DBAs use it to advance their SQL experience with modern tools to visualize and manage their databases, schemas, objects, and table data and to auto-generate, write and optimize queries. It has extended support for 30+ of the major databases and has basic-level support for all databases that can be accessed with a JDBC driver. DbVisualizer runs on all major OSes. Free and Pro versions are available.

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.

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.

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.

Apache DataFusion is a versatile and efficient query engine crafted in Rust, leveraging Apache Arrow for its in-memory data representation. It caters to developers engaged in creating data-focused systems, including databases, data frames, machine learning models, and real-time streaming applications. With its SQL and DataFrame APIs, DataFusion features a vectorized, multi-threaded execution engine that processes data streams efficiently and supports various partitioned data sources. It is compatible with several native formats such as CSV, Parquet, JSON, and Avro, and facilitates smooth integration with popular object storage solutions like AWS S3, Azure Blob Storage, and Google Cloud Storage. The architecture includes a robust query planner and an advanced optimizer that boasts capabilities such as expression coercion, simplification, and optimizations that consider distribution and sorting, along with automatic reordering of joins. Furthermore, DataFusion allows for extensive customization, enabling developers to incorporate user-defined scalar, aggregate, and window functions along with custom data sources and query languages, making it a powerful tool for diverse data processing needs. This adaptability ensures that developers can tailor the engine to fit their unique use cases effectively.

The Unified Analytics Warehouse. The Unified Analytics Warehouse is the best place to find high-performing analytics and machine learning at large scale. Tech research analysts are seeing new leaders as they strive to deliver game-changing big data analytics. Vertica empowers data-driven companies so they can make the most of their analytics initiatives. It offers advanced time-series, geospatial, and machine learning capabilities, as well as data lake integration, user-definable extensions, cloud-optimized architecture and more. Vertica's Under the Hood webcast series allows you to dive into the features of Vertica - delivered by Vertica engineers, technical experts, and others - and discover what makes it the most scalable and scalable advanced analytical data database on the market. Vertica supports the most data-driven disruptors around the globe in their pursuit for industry and business transformation.

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.

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

AlloyDB is a fully managed database service that is compatible with PostgreSQL, designed to meet the needs of the most demanding enterprise workloads. By merging Google's advancements with PostgreSQL, AlloyDB offers enhanced performance, scalability, and reliability. It ensures complete compatibility with PostgreSQL, allowing for both flexibility and genuine workload portability. For transactional workloads, its performance is up to four times faster than standard PostgreSQL, while it provides real-time analytical insights that are up to 100 times quicker. Additionally, AlloyDB AI supports the development of various generative AI applications. For versatile deployment, AlloyDB Omni is available as a downloadable version that can function in any environment. You can easily scale your resources and enjoy predictable performance, backed by a high availability service level agreement of 99.99%, which includes maintenance for the most intense enterprise demands. The automated systems, enhanced with machine learning capabilities, streamline management tasks such as database patching, backups, scaling, and replication, freeing users to focus on other priorities and innovations. This comprehensive approach makes AlloyDB a robust choice for organizations looking to optimize their database solutions.

Fujitsu Enterprise Postgres stands out as a highly dependable and powerful relational database tailored for businesses that demand exceptional query performance and consistent availability. Built on the acclaimed open-source platform PostgreSQL, it incorporates additional enterprise-level features that enhance both security and efficiency. The installation and management of Fujitsu Enterprise Postgres are handled by skilled database professionals from Fujitsu, who are also available to support the transition of data from your current database systems. Given its foundation in PostgreSQL, FEP offers remarkable compatibility with various systems and applications. Furthermore, the user-friendly, streamlined graphical interface significantly enhances the experience for database administrators carrying out essential functions like executing queries, conducting scans, and performing backups, ultimately making data management and reporting more user-friendly and effective. This comprehensive approach ensures that organizations can leverage their data to its fullest potential.

EMS SQL Management Studio for PostgreSQL offers a comprehensive suite for the administration and development of PostgreSQL databases. This all-in-one workbench equips users with essential tools for a variety of tasks, including managing databases and their components, designing databases, performing migrations, and building queries, as well as facilitating data import and export, comparing databases, and executing service tasks. Users can efficiently access and manage all databases and their associated objects through a streamlined console that features an intuitive interface. The software allows for the creation and modification of server and database objects, while enabling users to set required properties and examine detailed information using advanced visual editors. Additionally, with the Compare databases feature, users can automatically transfer structural changes from development environments to production databases. Users can also generate ER diagrams for newly constructed databases, facilitating expedited deployment. Setting up database maintenance tasks is made simple with advanced options, allowing SQL Studio to execute them on a regular schedule, ensuring optimal performance and reliability. This tool not only enhances productivity but also streamlines database management processes significantly.

RushDB is an innovative, open-source graph database that requires no configuration and rapidly converts JSON and CSV files into a fully normalized, queryable Neo4j graph, all while avoiding the complexities associated with schema design, migrations, and manual indexing. Tailored for contemporary applications as well as AI and machine learning workflows, RushDB offers an effortless experience for developers, merging the adaptability of NoSQL with the organized capabilities of relational databases. By incorporating automatic data normalization, ensuring ACID compliance, and featuring a robust API, RushDB streamlines the often challenging processes of data ingestion, relationship management, and query optimization, allowing developers to direct their energies toward building applications rather than managing databases. Some notable features include: 1. Instantaneous data ingestion without the need for configuration 2. Storage and querying capabilities powered by graph technology 3. Support for ACID transactions and seamless schema evolution 4. A developer-friendly API that facilitates querying akin to an SDK 5. High-performance capabilities for search and analytics 6. Flexibility to be self-hosted or cloud-compatible. This combination of features positions RushDB as a transformative solution in the realm of data management.

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.

A version of PostgreSQL enhanced with security, DBA, and Developer features as well as Oracle database compatibility. Kubernetes allows you to manage deployment, high availability, and automated failover. Postgres containers are lightweight and immutable, allowing you to deploy anywhere. Automate failover, switchovers, backups, recovery and rolling updates. You can move your images and operators to any cloud, so you don't have to be locked in. Our experts can help you overcome containerization and Kubernetes issues. Oracle compatibility allows you to leave your legacy database behind without having to start from scratch. Migrate client applications and databases faster with fewer problems. Tuning and boosting performance can improve the end-user's experience. Deployment on-premises or in the cloud is possible. In a world in which downtime can lead to revenue loss, High-Availability is essential for business continuity.

SurrealDB provides a versatile and flexible platform tailored for businesses. With a comprehensive array of advanced database solutions, tools, and services, SurrealDB enables teams to uncover creative solutions through products specifically designed to align with their needs. The query language utilized by SurrealDB bears a resemblance to traditional SQL, yet it is capable of handling time-series and interconnected graph data with ease. SurrealQL is a sophisticated query language that incorporates programming language features, empowering developers and data analysts to engage with SurrealDB in a manner that suits their preferences. Users can connect directly to SurrealDB from any client device, allowing them to execute SurrealQL queries straight within web browsers, which ensures that data access remains secure and permissions are upheld. The platform boasts highly efficient WebSocket connections that facilitate seamless bi-directional communication for queries, responses, and real-time notifications, enhancing the overall user experience. This ability to maintain constant connectivity and responsiveness sets SurrealDB apart in the realm of database solutions.

To address the challenges posed by sparse data, the Raijin Database adopts a flat JSON format for its data records. This database primarily utilizes SQL for querying while overcoming some of SQL's inherent restrictions. By employing data compression techniques, it not only conserves disk space but also enhances performance, particularly with contemporary CPU architectures. Many NoSQL options fall short in efficiently handling analytical queries or completely lack this functionality. However, Raijin DB facilitates group by operations and aggregations through standard SQL syntax. Its vectorized execution combined with cache-optimized algorithms enables the processing of substantial datasets effectively. Additionally, with the support of advanced SIMD instructions (SSE2/AVX2) and a modern hybrid columnar storage mechanism, it prevents CPU cycles from being wasted. Consequently, this results in exceptional data processing capabilities that outperform many alternatives, particularly those developed in higher-level or interpreted programming languages that struggle with large data volumes. This efficiency positions Raijin DB as a powerful solution for users needing to analyze and manipulate extensive datasets rapidly and effectively.

ProxySQL is engineered with a sophisticated multi-core framework that can handle hundreds of thousands of simultaneous connections while efficiently multiplexing them across numerous servers. It offers sharding capabilities based on user, schema, or table through its sophisticated query rule engine or customizable plugins. The development team is relieved from the need to alter queries generated by Object-Relational Mappers (ORMs) or packaged applications, as ProxySQL's dynamic query rewriting feature can adjust SQL statements as needed. The term "battle-tested" barely captures its resilience; ProxySQL has proven itself in the most demanding conditions. With performance as its core focus, the metrics speak for themselves. As an open-source, high-performance, and highly available proxy for MySQL and PostgreSQL, ProxySQL serves as a powerful SQL proxy solution, acting as a crucial intermediary between database clients and servers. This extensive array of features is designed to enhance and simplify database operations, ultimately allowing organizations to maximize their database infrastructure's effectiveness. The capabilities of ProxySQL ensure that organizations can achieve unparalleled efficiency and reliability in their database management tasks.

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.

Objectivity/DB (or Object Database Management System) is a distributed, highly scalable, high-performance, and highly scalable Object Database (ODBMS). It excels at complex data handling, including many types of connections between objects as well as many variants. Objectivity/DB can also be used as a graph database that is highly scalable and high-performance. Its DO query language allows for standard data retrieval queries and high-performance path-based navigational inquiries. Objectivity/DB is a distributed data base that presents a single logical view of its managed data. Data can be hosted on one machine or distributed over up to 65,000 machines. Machines can be connected to one another. Objectivity/DB can be used on 32- or 64-bit processors that run Windows, Linux, and Mac OS X. APIs are C++, C# Java, Python, and Java. All platforms and languages are interoperable. A C++ program on Linux can store objects and a Java program on Mac OS X can read them.

Amazon Aurora is a cloud-based relational database that is compatible with both MySQL and PostgreSQL, merging the high performance and reliability of traditional enterprise databases with the ease and affordability of open-source solutions. Its performance surpasses that of standard MySQL databases by as much as five times and outpaces standard PostgreSQL databases by three times. Additionally, it offers the security, availability, and dependability synonymous with commercial databases, all at a fraction of the cost—specifically, one-tenth. Fully managed by the Amazon Relational Database Service (RDS), Aurora simplifies operations by automating essential tasks such as hardware provisioning, database configuration, applying patches, and conducting backups. The database boasts a self-healing, fault-tolerant storage system that automatically scales to accommodate up to 64TB for each database instance. Furthermore, Amazon Aurora ensures high performance and availability through features like the provision of up to 15 low-latency read replicas, point-in-time recovery options, continuous backups to Amazon S3, and data replication across three distinct Availability Zones, which enhances data resilience and accessibility. This combination of features makes Amazon Aurora an appealing choice for businesses looking to leverage the cloud for their database needs while maintaining robust performance and security.

Serverless computing is particularly well-suited for applications that experience fluctuating loads. The automation of storage scaling, query execution, and backup processes simplifies management significantly. With serverless architecture, the service API's compatibility enables seamless integration with AWS SDKs across various programming languages such as Java, JavaScript, Node.js, .NET, PHP, Python, and Ruby. YDB is strategically hosted across three availability zones, ensuring continued availability even in the event of a node or zone failure. In situations where hardware or a data center encounters issues, the system is designed to recover automatically and maintain operational continuity. YDB is optimized for high-performance environments, capable of handling hundreds of thousands of transactions each second while keeping latency minimal. Additionally, the architecture has been specifically developed to support the management of vast data volumes, accommodating hundreds of petabytes efficiently. This robust design makes it an exceptional choice for businesses requiring reliability and speed in their data processing needs.

BigchainDB functions as a database infused with blockchain features, offering high throughput, low latency, advanced query capabilities, decentralized governance, permanent data storage, and integrated asset management. This platform enables both developers and businesses to create blockchain proof-of-concepts, applications, and platforms, catering to a diverse array of industries and practical applications. Instead of enhancing existing blockchain technology, BigchainDB uniquely merges a large-scale distributed database with blockchain traits—such as decentralized governance, data immutability, and digital asset transfer. Its architecture eliminates any single point of control or failure, utilizing a federation of voting nodes to establish a peer-to-peer network. Users can execute any MongoDB query to sift through the entirety of stored transactions, assets, metadata, and blocks, leveraging the robust capabilities of MongoDB as its backbone. This innovative approach not only streamlines data management but also enriches the user experience by ensuring reliability and efficiency in digital asset transactions.

dbForge Studio for PostgreSQL is a GUI tool for database development and management. The IDE for PostgreSQL allows users to create, develop, and execute queries, edit and adjust the code to your requirements in a convenient and user-friendly interface. SQL Development Save your time and improve code quality when creating and editing queries. Explorer Navigate through the object tree and find any PostgreSQL object you are interested in. Data Editor Users can manage the settings of tables. Data Export and Import Supports 10+ widely used data formats, a number of advanced options, and templates for recurring scenarios. Query Profiler It allows you to identify queries with the longest duration, analyze whether they can be optimized, and compare the results before and after optimization. Data and Schema Compare The tool allows to compare and synchronize PostgreSQL database data and schemas, and synchronize tables between PostgreSQL and Redshift databases. Data Generator Designed to generate huge amounts of realistic test data and accurately visualize the generated data in real time. Pivot Table Visual Pivot Table Designer, advanced filtering, visual data presentation in a graph.

Databend is an innovative, cloud-native data warehouse crafted to provide high-performance and cost-effective analytics for extensive data processing needs. Its architecture is elastic, allowing it to scale dynamically in response to varying workload demands, thus promoting efficient resource use and reducing operational expenses. Developed in Rust, Databend delivers outstanding performance through features such as vectorized query execution and columnar storage, which significantly enhance data retrieval and processing efficiency. The cloud-first architecture facilitates smooth integration with various cloud platforms while prioritizing reliability, data consistency, and fault tolerance. As an open-source solution, Databend presents a versatile and accessible option for data teams aiming to manage big data analytics effectively in cloud environments. Additionally, its continuous updates and community support ensure that users can take advantage of the latest advancements in data processing technology.

Percona Distribution for PostgreSQL provides an enterprise-grade, open-source installation of PostgreSQL Core Distribution and critical additional enterprise components. PostgreSQL Core Distribution supports a wide variety of data types and user-defined object. It is ACID-compliant. PostgreSQL Core distribution is a stable, secure, open-source product that many organizations rely on. PostgreSQL Core Distribution is a reliable open-source product that can be relied upon by multiple organizations. Percona Distribution is installed for PostgreSQL. This means you have everything you need to get PostgreSQL up and running, including pg_repack and pgaudit and pgBackRest. Percona Distribution for PostgreSQL provides all of this in one installation. All components have been tested together and are updated as needed.

Hydra is an innovative, open-source solution that transforms Postgres into a column-oriented database, enabling instant queries over billions of rows without necessitating any alterations to your existing code. By employing advanced techniques such as parallelization and vectorization for aggregate functions like COUNT, SUM, and AVG, Hydra significantly enhances the speed and efficiency of data processing in Postgres. In just five minutes, you can set up Hydra without modifying your syntax, tools, data model, or extensions, ensuring a hassle-free integration. For those seeking a fully managed experience, Hydra Cloud offers seamless operations and optimal performance. Various industries can benefit from tailored analytics by leveraging powerful Postgres extensions and custom functions, allowing you to take charge of your data needs. Designed with user requirements in mind, Hydra stands out as the fastest Postgres solution available for analytical tasks, making it an essential tool for data-driven decision-making. With features like columnar storage, query parallelization, and vectorization, Hydra is poised to redefine the analytics landscape.

Modern native client with intuitive GUI tools to access, query, and edit multiple databases: MySQL. PostgreSQL. SQLite. Microsoft SQL Server. Amazon Redshift. MariaDB. CockroachDB. Vertica. Snowflake. Oracle. Redis.

SQLAI simplifies database management by converting plain language into SQL queries, allowing users to quickly generate complex queries for MySQL, PostgreSQL, and other major databases. The platform offers advanced features like query optimization, automatic error correction, and performance analysis, ensuring that queries are efficient and secure. SQLAI is ideal for developers, data analysts, and database administrators who want to reduce manual SQL work and enhance productivity with AI-powered solutions.

For macOS users seeking a PostgreSQL GUI tool, PSequel stands out with its straightforward and user-friendly interface, allowing users to efficiently execute common PostgreSQL tasks. While pgAdmin is known for its extensive features, it often suffers from a cumbersome and complex user interface. Although there are numerous PostgreSQL GUI tools available, many of them rely on web or Java technologies, or they lack essential features that users desire. In the realm of MySQL, Sequel Pro is often regarded as the top client; however, it has not made strides in supporting PostgreSQL. This gap inspired us to create PSequel, which is built from the ground up using Swift 2, drawing significant inspiration from the design of Sequel Pro. Currently, PSequel is a passion project that we are developing in our free time. By focusing exclusively on macOS versions 10.10 and above, we aim to streamline the codebase and reduce the need for testing on outdated systems, resulting in a more efficient and less error-prone application. As PSequel continues to evolve, we are excited about the potential enhancements and features that will be introduced in future updates. The project remains in its early development phase, promising a bright future for PostgreSQL users on macOS.

Prioritize application innovation rather than database oversight by utilizing the fully managed and intelligent Azure Database for PostgreSQL service. Effortlessly scale your workloads while maintaining confidence in performance. Benefit from remarkable high availability, guaranteed by a service-level agreement (SLA) that promises up to 99.99 percent uptime, and select between same-zone or zone-redundant high availability options, coupled with AI-driven performance insights and robust enterprise security features. Concentrate on application development with a PostgreSQL database offered as a managed service. The zone-redundant high availability feature streamlines maintenance, patching, and updates for your convenience. Set up your database in mere minutes and adjust compute or storage resources independently as needed. Reduce expenses with extensive database monitoring and optimization resources that ensure efficiency. Leverage intelligent performance recommendations to maintain optimal application functionality. Seamlessly migrate your data using a fully managed PostgreSQL database that supports the latest versions and technologies. Moreover, enhance your projects with popular PostgreSQL extensions, including Cron, PostGIS, PLV8, and more, to unlock a wider range of functionalities.

Explore, create, and manage databases utilizing Valentina DB, MySQL, MariaDB, PostgreSQL, and SQLite at no cost. Generate comprehensive business reports through Valentina Studio Pro, either on Valentina Server or within an application that utilizes an Application Developer Kit. Engage in backward engineering with standard practices while also employing forward engineering techniques in Valentina Studio Pro. Conduct reverse engineering to produce diagrams for pre-existing databases, and easily integrate new elements into these diagrams. Write SQL queries with features such as auto-completion and syntax highlighting, while also defining and managing favorite queries and accessing recent ones seamlessly. Benefit from a function browser that provides a dictionary for each SQL function as well as consoles that report errors, warnings, and performance metrics. Efficiently search and export result records in various formats including CSV, JSON, and Excel, while simultaneously editing the properties of multiple database objects. Delve deep into tables and fields with remarkable speed, and manage the addition or removal of users and groups, along with their associated privileges. This multifaceted approach ensures that users can handle database management with efficiency and effectiveness.

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.

Provides the full range of features found in on-premises Informix deployments, but with reduced cost, complexity, and risk associated with infrastructure management. The IBM® Informix® on Cloud solution delivers an Informix database hosted on IBM Cloud®, allowing customers to enjoy the extensive capabilities of an on-premises setup while minimizing the challenges of infrastructure upkeep. With Informix on Cloud, users benefit from a high-performance engine that seamlessly combines time series, spatial, NoSQL, and SQL data, along with convenient access via MQTT, REST, and MongoDB APIs. This offering not only simplifies and accelerates cloud deployments but also harnesses the superior performance of the Informix engine, which is designed to integrate diverse data types effortlessly. By leveraging flexible hosting options and adaptable software licensing, businesses can lower their infrastructure maintenance costs and streamline operational complexity, all while selecting the size that best fits their specific requirements, backed by continuous support. This makes Informix on Cloud an ideal choice for organizations looking to modernize their data management strategies without the traditional burdens of self-hosting.

Blueflood is an advanced distributed metric processing system designed for high throughput and low latency, operating as a multi-tenant solution that supports Rackspace Metrics. It is actively utilized by both the Rackspace Monitoring team and the Rackspace public cloud team to effectively manage and store metrics produced by their infrastructure. Beyond its application within Rackspace, Blueflood also sees extensive use in large-scale deployments documented in community resources. The data collected through Blueflood is versatile, allowing users to create dashboards, generate reports, visualize data through graphs, or engage in any activities that involve analyzing time-series data. With a primary emphasis on near-real-time processing, data can be queried just milliseconds after it is ingested, ensuring timely access to information. Users send their metrics to the ingestion service and retrieve them from the Query service, while the system efficiently handles background rollups through offline batch processing, thus facilitating quick responses for queries covering extended time frames. This architecture not only enhances performance but also ensures that users can rely on rapid access to their critical metrics for effective decision-making.

When PostgreSQL serves as the foundation of your enterprise and is a key data source, PeerDB offers an efficient, straightforward, and economical solution for replicating data from PostgreSQL to data warehouses, queues, and storage systems. It is engineered to function seamlessly at any scale and is specifically adapted for various data repositories. By utilizing replication messages sourced from the PostgreSQL replication slot, PeerDB adeptly replays schema updates while providing alerts for slot growth and active connections. It also includes native support for PostgreSQL toast columns and large JSONB columns, making it particularly advantageous for IoT applications. The platform features an optimized query architecture aimed at minimizing warehouse expenditures, which is especially beneficial for users of Snowflake and BigQuery. Additionally, it accommodates partitioned tables through both publication mechanisms. PeerDB ensures rapid and reliable initial data loads via transaction snapshotting and CTID scanning techniques. With features such as high availability, in-place upgrades, autoscaling, advanced logging, comprehensive metrics, and monitoring dashboards, as well as burstable instance types, it is also well-suited for development environments. Overall, PeerDB stands out as a versatile tool that effectively meets the diverse needs of modern data management.

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.

PartiQL extends SQL in a manner that is straightforward, allowing nested data to be treated as integral components and enabling a smooth integration with SQL itself. This capability facilitates intuitive operations such as filtering, joining, and aggregating various types of data, including structured, semistructured, and nested datasets. By decoupling the syntax and semantics of queries from the actual data format or storage system, PartiQL provides a cohesive querying experience across diverse data stores and formats. It empowers users to engage with data irrespective of the presence of a standard schema. Additionally, the components of PartiQL—including its syntax, semantics, embedded reference interpreter, command-line interface, testing framework, and associated tests—are distributed under the Apache License, version 2.0. This licensing grants users the freedom to use, modify, and share their contributions while adhering to their preferred terms. Thus, the overall design of PartiQL enhances accessibility and flexibility in data management across various platforms.

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.

dbForge Edge is the newest Devart product - the multidatabase software solution covers all database-related jobs, allowing its users to accelerate the tasks' completion, save costs, and improve overall productivity. A set of powerful features applies to all most popular database management systems - MySQL and MariaDB, SQL Server, Oracle, and PostgreSQL. Notice the most helpful features of dbForge Edge: Database design & development. Data and schema management. Data analysis. Reporting. Database administration.

The software significantly reduces the effort, expenses, and risks associated with transferring data between various database formats, including Oracle, MySQL, MariaDB, SQL Server, PostgreSQL, IBM DB2, IBM Informix, InterSystems Caché, Teradata, Visual Foxpro, SQLite, FireBird, InterBase, Microsoft Access, Microsoft Excel, Paradox, Lotus, dBase, CSV/Text, and any ODBC DSN data source. By leveraging this tool, you can streamline the migration process for numerous data types, structures, and objects, ultimately leading to substantial savings in both time and financial resources. It seamlessly handles the automatic migration of table structures, data, schemas (for databases like Oracle, SQL Server 2000 or later, PostgreSQL, and IBM DB2), LOBs (Large Objects), primary and foreign keys, indexes, auto-increment values, comments, default values, and much more. Additionally, the software supports migrations between different character sets, such as UTF8 and CP1250, and it intelligently converts various data encodings. Users also have the flexibility to modify field names, data types, nullable options, precision, and numscale, as well as filter data during the migration process for enhanced customization and control. This versatility makes it an invaluable tool for any organization looking to optimize their data management strategies.

A vector database designed for scalable similarity searches. Open-source, highly scalable and lightning fast. Massive embedding vectors created by deep neural networks or other machine learning (ML), can be stored, indexed, and managed. Milvus vector database makes it easy to create large-scale similarity search services in under a minute. For a variety languages, there are simple and intuitive SDKs. Milvus is highly efficient on hardware and offers advanced indexing algorithms that provide a 10x speed boost in retrieval speed. Milvus vector database is used in a variety a use cases by more than a thousand enterprises. Milvus is extremely resilient and reliable due to its isolation of individual components. Milvus' distributed and high-throughput nature makes it an ideal choice for large-scale vector data. Milvus vector database uses a systemic approach for cloud-nativity that separates compute and storage.

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.

DbSchema is an innovative tool designed for collaborative visual schema design, deployment, and documentation within teams. Its various integrated features, such as data exploration, a visual query editor, and data generator, make it an essential resource for anyone working with databases on a daily basis. Supporting a wide range of both relational and No-SQL databases—including MySQL, PostgreSQL, SQLite, Microsoft SQL Server, MongoDB, MariaDB, Redshift, Snowflake, and Google—DbSchema caters to diverse database needs. One of its standout capabilities is reverse-engineering database schemas and representing them visually through diagrams. Users can engage with their databases through these diagrams and other visual tools. The DbSchema model maintains its version of the schema structure, which is distinct from the actual database, enabling seamless deployment across various databases. This feature allows users to save design models as files, store them in GIT, and collaborate on schema design without needing a direct database connection. Additionally, users can easily compare different schema versions and generate SQL migration scripts, enhancing their workflow efficiency. Ultimately, DbSchema empowers teams to streamline their database management processes effectively.

A streaming database is specifically designed to efficiently ingest, store, process, and analyze large volumes of data streams. This advanced data infrastructure integrates messaging, stream processing, and storage to enable real-time value extraction from your data. It continuously handles vast amounts of data generated by diverse sources, including sensors from IoT devices. Data streams are securely stored in a dedicated distributed streaming data storage cluster that can manage millions of streams. By subscribing to topics in HStreamDB, users can access and consume data streams in real-time at speeds comparable to Kafka. The system also allows for permanent storage of data streams, enabling users to replay and analyze them whenever needed. With a familiar SQL syntax, you can process these data streams based on event-time, similar to querying data in a traditional relational database. This functionality enables users to filter, transform, aggregate, and even join multiple streams seamlessly, enhancing the overall data analysis experience. Ultimately, the integration of these features ensures that organizations can leverage their data effectively and make timely decisions.