Greenplum Alternatives

BigQuery is a serverless, multicloud data warehouse that simplifies the process of working with all types of data so you can focus on getting valuable business insights quickly. At the core of Google’s data cloud, BigQuery allows you to simplify data integration, cost effectively and securely scale analytics, share rich data experiences with built-in business intelligence, and train and deploy ML models with a simple SQL interface, helping to make your organization’s operations more data-driven.

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, 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. • Gain critical real-time insights to run your business • Seamlessly integrate data streaming and batch data • High performance in throughput and low-latency at petabyte scale • Fully-managed cloud service • Tiered storage to optimize cloud performance & spend • Fully-secure & enterprise-ready

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. Easily provision, monitor, backup and scale your open source databases with high availability, advanced security, full superuser and SSH access, query analysis, and troubleshooting support to improve the performance of your deployments. Supported databases include: - MySQL - PostgreSQL - Redis™ - MongoDB® database - Greenplum™ (coming soon) The ScaleGrid platform supports both public and private clouds, including AWS, Azure, Google Cloud Platform (GCP), DigitalOcean, Linode, Oracle Cloud Infrastructure (OCI), VMware and OpenStack. Used by thousands of developers, startups, and enterprise customers including Atlassian, Meteor, and Accenture, ScaleGrid handles all your database operations at any scale so you can focus on your application performance.

More customers pick Amazon Redshift than any other cloud data warehouse. Redshift powers analytical workloads for Fortune 500 companies, startups, and everything in between. Companies like Lyft have grown with Redshift from startups to multi-billion dollar enterprises. No other data warehouse makes it as easy to gain new insights from all your data. With Redshift you can query petabytes of structured and semi-structured data across your data warehouse, operational database, and your data lake using standard SQL. Redshift lets you easily save the results of your queries back to your S3 data lake using open formats like Apache Parquet to further analyze from other analytics services like Amazon EMR, Amazon Athena, and Amazon SageMaker. Redshift is the world’s fastest cloud data warehouse and gets faster every year. For performance intensive workloads you can use the new RA3 instances to get up to 3x the performance of any cloud data warehouse.

Google Cloud Bigtable is a fully managed, scalable NoSQL database service for large analytical and operational workloads. Fast and performant: Use Cloud Bigtable as the storage engine that grows with you from your first gigabyte to petabyte-scale for low-latency applications as well as high-throughput data processing and analytics. Seamless scaling and replication: Start with a single node per cluster, and seamlessly scale to hundreds of nodes dynamically supporting peak demand. Replication also adds high availability and workload isolation for live serving apps. Simple and integrated: Fully managed service that integrates easily with big data tools like Hadoop, Dataflow, and Dataproc. Plus, support for the open source HBase API standard makes it easy for development teams to get started.

ClickHouse is a fast open-source OLAP database management system. It is column-oriented and allows to generate analytical reports using SQL queries in real-time. ClickHouse's performance exceeds comparable column-oriented database management systems currently available on the market. It processes hundreds of millions to more than a billion rows and tens of gigabytes of data per single server per second. ClickHouse uses all available hardware to its full potential to process each query as fast as possible. Peak processing performance for a single query stands at more than 2 terabytes per second (after decompression, only used columns). In distributed setup reads are automatically balanced among healthy replicas to avoid increasing latency. ClickHouse supports multi-master asynchronous replication and can be deployed across multiple datacenters. All nodes are equal, which allows avoiding having single points of failure.

MariaDB Platform is a complete enterprise open source database solution. It has the versatility to support transactional, analytical and hybrid workloads as well as relational, JSON and hybrid data models. And it has the scalability to grow from standalone databases and data warehouses to fully distributed SQL for executing millions of transactions per second and performing interactive, ad hoc analytics on billions of rows. MariaDB can be deployed on prem on commodity hardware, is available on all major public clouds and through MariaDB SkySQL as a fully managed cloud database. To learn more, visit mariadb.com.

The Open, Multi-Cloud Stack for Modern Data Apps. Built on open-source Apache Cassandra™. Global-scale and 100% uptime without vendor lock-in. Deploy on multi-cloud, on-prem, open-source, and Kubernetes. Elastic and pay-as-you-go for improved TCO. Start building faster with Stargate APIs for NoSQL, real-time, reactive, JSON, REST, and GraphQL. Skip the complexity of multiple OSS projects and APIs that don’t scale. Ideal for commerce, mobile, AI/ML, IoT, microservices, social, gaming, and richly interactive applications that must scale-up and scale-down with demand. Get building modern data applications with Astra, a database-as-a-service powered by Apache Cassandra™. Use REST, GraphQL, JSON with your favorite full-stack framework Richly interactive apps that are elastic and viral-ready from Day 1. Pay-as-you-go Apache Cassandra DBaaS that scales effortlessly and affordably.

The Unified Analytics Warehouse. Highest performing analytics and machine learning at extreme scale. As the criteria for data warehousing continues to evolve, tech research analysts are seeing new leaders in the drive for game-changing big data analytics. Vertica powers data-driven enterprises so they can get the most out of their analytics initiatives with advanced time-series and geospatial analytics, in-database machine learning, data lake integration, user-defined extensions, cloud-optimized architecture, and more. Our Under the Hood webcast series lets you to dive deep into Vertica features – delivered by Vertica engineers and technical experts – to find out what makes it the fastest and most scalable advanced analytical database on the market. From ride sharing apps and smart agriculture to predictive maintenance and customer analytics, Vertica supports the world’s leading data-driven disruptors in their pursuit of industry and business transformation.

Apache Druid is an open source distributed data store. Druid’s core design combines ideas from data warehouses, timeseries databases, and search systems to create a high performance real-time analytics database for a broad range of use cases. Druid merges key characteristics of each of the 3 systems into its ingestion layer, storage format, querying layer, and core architecture. Druid stores and compresses each column individually, and only needs to read the ones needed for a particular query, which supports fast scans, rankings, and groupBys. Druid creates inverted indexes for string values for fast search and filter. Out-of-the-box connectors for Apache Kafka, HDFS, AWS S3, stream processors, and more. Druid intelligently partitions data based on time and time-based queries are significantly faster than traditional databases. Scale up or down by just adding or removing servers, and Druid automatically rebalances. Fault-tolerant architecture routes around server failures.

We make BI & Big Data analytics work easier and faster. Our goal is to empower business users and make always-busy business and heavily loaded BI specialists less dependent on each other when solving data-driven business problems. If you have ever experienced a lack of data you needed, time to consuming report generation or long queue to your BI expert, consider Querona. Querona uses a built-in Big Data engine to handle growing data volumes. Repeatable queries can be cached or calculated in advance. Optimization needs less effort as Querona automatically suggests query improvements. Querona empowers business analysts and data scientists by putting self-service in their hands. They can easily discover and prototype data models, add new data sources, experiment with query optimization and dig in raw data. Less IT is needed. Now users can get live data no matter where it is stored. If databases are too busy to be queried live, Querona will cache the data.

The enterprise database for time series, documents, and vectors. Store any type of data and combine the simplicity of SQL with the scalability of NoSQL. CrateDB is an open source distributed database running queries in milliseconds, whatever the complexity, volume and velocity of data.

The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance. Linear scalability and proven fault-tolerance on commodity hardware or cloud infrastructure make it the perfect platform for mission-critical data. Cassandra's support for replicating across multiple datacenters is best-in-class, providing lower latency for your users and the peace of mind of knowing that you can survive regional outages.

Choose from a wide range of SQL features to realise your applications from pure analytics to hybrid transactional/analytical processing. When you're curious about what's in your data; when you want to work efficiently; when your deadline is closing: MonetDB returns query result in mere seconds or even less. When you want to (re)use your own code; when you need specialised functions: use the hooks to add your own user-defined functions in SQL, Python, R or C/C++. Join us and expand the MonetDB community spread over 130+ countries with students, teachers, researchers, start-ups, small businesses and multinational enterprises. Join the leading Database in Analytical Jobs and surf the innovation! Don’t lose time with complex installation, use MonetDB’s easy setup to get your DBMS up and running quickly.

Real-Time Analytics on Raw Data. Live ingest from S3, Kafka, DynamoDB & more. Explore raw data as SQL tables. Build amazing data-driven applications & live dashboards in minutes. Rockset is a serverless search and analytics engine that powers real-time apps and live dashboards. Operate directly on raw data, including JSON, XML, CSV, Parquet, XLSX or PDF. Plug data from real-time streams, data lakes, databases, and data warehouses into Rockset. Ingest real-time data without building pipelines. Rockset continuously syncs new data as it lands in your data sources without the need for a fixed schema. Use familiar SQL, including joins, filters, and aggregations. It’s blazing fast, as Rockset automatically indexes all fields in your data. Serve fast queries that power the apps, microservices, live dashboards, and data science notebooks you build. Scale without worrying about servers, shards, or pagers.

Hypertable delivers scalable database capacity at maximum performance to speed up your big data application and reduce your hardware footprint. Hypertable delivers maximum efficiency and superior performance over the competition which translates into major cost savings. A proven scalable design that powers hundreds of Google services. All the benefits of open source with a strong and thriving community. C++ implementation for optimum performance. 24/7/365 support for your business-critical big data application. Unparalleled access to Hypertable brain power by the employer of all core Hypertable developers. Hypertable was designed for the express purpose of solving the scalability problem, a problem that is not handled well by a traditional RDBMS. Hypertable is based on a design developed by Google to meet their scalability requirements and solves the scale problem better than any of the other NoSQL solutions out there.

Sadas Engine is the fastest Columnar Database Management System both in Cloud and On Premise. Turn Data into Information with the fastest columnar Database Management System able to perform 100 times faster than transactional DBMSs and able to carry out searches on huge quantities of data over a period even longer than 10 years. Every day we work to ensure impeccable service and appropriate solutions to enhance the activities of your specific business. SADAS srl, a company of the AS Group , is dedicated to the development of Business Intelligence solutions, data analysis applications and DWH tools, relying on cutting-edge technology. The company operates in many sectors: banking, insurance, leasing, commercial, media and telecommunications, and in the public sector. Innovative software solutions for daily management needs and decision-making processes, in any sector

QikkDB is a GPU accelerated columnar database, delivering stellar performance for complex polygon operations and big data analytics. When you count your data in billions and want to see real-time results you need qikkDB. We support Windows and Linux operating systems. We use Google Tests as the testing framework. There are hundreds of unit tests and tens of integration tests in the project. For development on Windows, Microsoft Visual Studio 2019 is recommended, and its dependencies are CUDA version 10.2 minimal, CMake 3.15 or newer, vcpkg, boost. For development on Linux, the dependencies are CUDA version 10.2 minimal, CMake 3.15 or newer, and boost. This project is licensed under the Apache License, Version 2.0. You can use an installation script or dockerfile to install qikkDB.

GeoSpock enables data fusion for the connected world with GeoSpock DB – the space-time analytics database. GeoSpock DB is a unique, cloud-native database optimised for querying for real-world use cases, able to fuse multiple sources of Internet of Things (IoT) data together to unlock its full value, whilst simultaneously reducing complexity and cost. GeoSpock DB enables efficient storage, data fusion, and rapid programmatic access to data, and allows you to run ANSI SQL queries and connect to analytics tools via JDBC/ODBC connectors. Users are able to perform analysis and share insights using familiar toolsets, with support for common BI tools (such as Tableau™, Amazon QuickSight™, and Microsoft Power BI™), and Data Science and Machine Learning environments (including Python Notebooks and Apache Spark). The database can also be integrated with internal applications and web services – with compatibility for open-source and visualisation libraries such as Kepler and Cesium.js.

Using DBHawk, our customers were able to comply with GDPR, HIPAA, SOX, GLBA, and other regulations and were able to implement SOD. Self-Service BI & Ad-Hoc Reporting Tool with feature to define Data Access Policy, Connect to multiple Data sources, Build Powerful SQL Charts and data Dashboards. DBHawk SQL editor is an advanced editor that allows users to build, edit, and run database queries with a web-based interface. DBHawk Query Builder is supported with all major databases such as Oracle, Microsoft SQL Server, PostgreSQL, Greenplum, MySQL, DB2, Amazon Redshift, Hive, Amazon Athena. Database SQL tasks and batch job automation with a web-based centralized tool. Secure access to SQL, NoSQL and Cloud databases with our all-in-one data platform. Trusted by our customers to protect and access their data. Centralized Security, Auditing and insights about your user’s activities.

InfiniDB is a column-store DBMS optimized for OLAP workloads. It has a distributed architecture to support Massive Paralllel Processing (MPP). It uses MySQL as its front-end such that users familiar with MySQL can quickly migrate to InfiniDB. Due to this fact, users can connect to InfiniDB using any MySQL connector. InfiniDB applies MVCC to do concurrency control. It uses term System Change Number (SCN) to indicate a version of the system. In its Block Resolution Manager (BRM), it utilizes three structures, version buffer, version substitution structure, and version buffer block manager, to manage multiple versions. InfiniDB applies deadlock detection to resolve conflicts. InfiniDB uses MySQL as its front-end and supports all MySQL syntaxes, including foreign keys. InfiniDB is a columnar DBMS. For each column, InfiniDB applies range partitioning and stores the minimum and maximum value of each partition in a small structure called extent map.

Your cloud data platform. Secure and easy access to any data with infinite scalability. Get all the insights from all your data by all your users, with the instant and near-infinite performance, concurrency and scale your organization requires. Seamlessly share and consume shared data to collaborate across your organization, and beyond, to solve your toughest business problems in real time. Boost the productivity of your data professionals and shorten your time to value in order to deliver modern and integrated data solutions swiftly from anywhere in your organization. Whether you’re moving data into Snowflake or extracting insight out of Snowflake, our technology partners and system integrators will help you deploy Snowflake for your success.

PolarDB-X has been tried and tested in Tmall Double 11 shopping festivals, and has helped customers in industries such as finance, logistics, energy, e-commerce, and public service to address business challenges. Linearly increases storage space to provide petabyte-scale storage, making storage bottlenecks of standalone databases a thing of the past. Provides the massively parallel processing (MPP) capabilities to significantly improve the efficiency of complex analysis and queries on vast amounts of data. Provides extensive algorithms to distribute data across multiple storage nodes, effectively reducing the volume of data stored in a single table.

Directus is an Open Data Platform for managing the content of any SQL database. It provides a powerful API layer for developers and an intuitive App for non-technical users. Written entirely in JavaScript (primarily Node.js and Vue.js), Directus is completely open-source, modular, and extensible, allowing it to be fully tailored to your exact project needs. With Directus Cloud, we've taken our open-source spirit to the cloud by offering Directus Community Cloud, a completely free tier - without quotas or limitations. It's ideal for hobby projects and demos, and when you're ready for production, Standard Cloud has the power and infrastructure options you need. Our pricing is usage-based, which means you only pay for what you use. Use Directus on your next headless cms, internal tool, or SaaS project, or use our Insights for better data management and analytics. With Directus, you're only limited by your imagination.

Trino is a query engine that runs at ludicrous speed. Fast-distributed SQL query engine for big data analytics that helps you explore your data universe. Trino is a highly parallel and distributed query engine, that is built from the ground up for efficient, low-latency analytics. The largest organizations in the world use Trino to query exabyte-scale data lakes and massive data warehouses alike. Supports diverse use cases, ad-hoc analytics at interactive speeds, massive multi-hour batch queries, and high-volume apps that perform sub-second queries. Trino is an ANSI SQL-compliant query engine, that works with BI tools such as R, Tableau, Power BI, Superset, and many others. You can natively query data in Hadoop, S3, Cassandra, MySQL, and many others, without the need for complex, slow, and error-prone processes for copying the data. Access data from multiple systems within a single query.

Hydra is an open source, column-oriented Postgres. Query billions of rows instantly, no code changes. Hydra parallelizes and vectorizes aggregates (COUNT, SUM, AVG) to deliver the speed you’ve always wanted on Postgres. Boost performance at every size! Set up Hydra in 5 minutes without changing your syntax, tools, data model, or extensions. Use Hydra Cloud for fully managed operations and smooth sailing. Different industries have different needs. Get better analytics with powerful Postgres extensions, custom functions, and take control. Built by you, for you. Hydra is the fastest Postgres in the market for analytics. Boost performance with columnar storage, vectorization, and query parallelization.

HeatWave is a massively parallel, high performance, in-memory query accelerator for Oracle MySQL Database Service that accelerates MySQL performance by orders of magnitude for analytics and mixed workloads. HeatWave is 6.5X faster than Amazon Redshift at half the cost, 7X faster than Snowflake at one-fifth the cost, and 1400X faster than Amazon Aurora at half the cost. MySQL Database Service with HeatWave is the only service that enables customers to run OLTP and OLAP workloads directly from their MySQL database. This eliminates the need for complex, time-consuming, and expensive data movement and integration with a separate analytics database. The new MySQL Autopilot uses advanced machine-learning techniques to automate HeatWave, which make it easier to use and further improves performance and scalability. HeatWave is optimized for Oracle Cloud Infrastructure (OCI).

Fujitsu Enterprise Postgres is an exceptionally reliable and robust relational database, created for organizations that require strong query performance and high availability. It is based on the world-renowned open-source system — PostgreSQL, with additional enterprise-grade features for enhanced security and better performance. Fujitsu Enterprise Postgres is installed and operated by Fujitsu’s database experts who can also assist with the migration of data from your existing database. Based on PostgreSQL, FEP is highly compatible with other systems and applications. The simple, clean graphic user interface improves the experience for DBAs executing core database functions, such as running queries, scanning, and back-up, making your data and reporting more accessible.

LanceDB is a developer-friendly, open source database for AI. From hyperscalable vector search and advanced retrieval for RAG to streaming training data and interactive exploration of large-scale AI datasets, LanceDB is the best foundation for your AI application. Installs in seconds and fits seamlessly into your existing data and AI toolchain. An embedded database (think SQLite or DuckDB) with native object storage integration, LanceDB can be deployed anywhere and easily scales to zero when not in use. From rapid prototyping to hyper-scale production, LanceDB delivers blazing-fast performance for search, analytics, and training for multimodal AI data. Leading AI companies have indexed billions of vectors and petabytes of text, images, and videos, at a fraction of the cost of other vector databases. More than just embedding. Filter, select, and stream training data directly from object storage to keep GPU utilization high.

ScyllaDB is the database for data-intensive apps that require high performance and low latency. It enables teams to harness the ever-increasing computing power of modern infrastructures – eliminating barriers to scale as data grows. Unlike any other database, ScyllaDB is a distributed NoSQL database fully compatible with Apache Cassandra and Amazon DynamoDB, yet is built with deep architectural advancements that enable exceptional end-user experiences at radically lower costs. Over 400 game-changing companies like Disney+ Hotstar, Expedia, FireEye, Discord, Zillow, Starbucks, Comcast, and Samsung use ScyllaDB for their toughest database challenges. ScyllaDB is available as free open source software, a fully-supported enterprise product, and a fully managed database-as-a-service (DBaaS) on multiple cloud providers.

FairCom DB is ideal for large-scale, mission-critical, core-business applications that require performance, reliability and scalability that cannot be achieved by other databases. FairCom DB delivers predictable high-velocity transactions and massively parallel big data analytics. It empowers developers with NoSQL APIs for processing binary data at machine speed and ANSI SQL for easy queries and analytics over the same binary data. Among the companies that take advantage of the flexibility of FairCom DB is Verizon, who recently chose FairCom DB as an in-memory database for its Verizon Intelligent Network Control Platform Transaction Server Migration. FairCom DB is an advanced database engine that gives you a Continuum of Control to achieve unprecedented performance with the lowest total cost of ownership (TCO). You do not conform to FairCom DB…FairCom DB conforms to you. With FairCom DB, you are not forced to conform your needs to meet the limitations of the database.

Analyze the performance of Greenplum DBMS using monitoring and query management tools in the command center, where you can also view and download query and session histories. Hybrid Storage in Yandex Managed Service for Greenplum® is natively integrated with Object Storage, allowing you to organize hybrid storage with automatic data transfers to cold storage. You can deploy a ready-to-use cluster in just a few minutes. DB settings are optimized for the selected cluster size and you can change them if necessary. Thanks to its integration with the DataLens BI system, build reports, charts, and dashboards, directly from the service, based on data stored in Greenplum. All DBMS connections are encrypted using the TLS protocol. Our infrastructure meets local regulatory, GDPR, industry-specific ISO standards, and PCI DSS security requirements.

Vector database built for scalable similarity search. Open-source, highly scalable, and blazing fast. Store, index, and manage massive embedding vectors generated by deep neural networks and other machine learning (ML) models. With Milvus vector database, you can create a large-scale similarity search service in less than a minute. Simple and intuitive SDKs are also available for a variety of different languages. Milvus is hardware efficient and provides advanced indexing algorithms, achieving a 10x performance boost in retrieval speed. Milvus vector database has been battle-tested by over a thousand enterprise users in a variety of use cases. With extensive isolation of individual system components, Milvus is highly resilient and reliable. The distributed and high-throughput nature of Milvus makes it a natural fit for serving large-scale vector data. Milvus vector database adopts a systemic approach to cloud-nativity, separating compute from storage.

Quest Database Management Solutions. Today’s database technology is becoming increasingly complex, and supports previously unthinkable data volumes – all driven by the demands of today’s always-on economy. This drives most organizations to spend up to 65% of their time just keeping the lights on, leaving very little time to deliver innovations that move the business forward. Digital transformation initiatives such as cloud migration, DevOps, open-source database adoption and data privacy require commitment and time from IT at a time when they are already under huge pressure to maintain service levels. It’s time for a new approach. Spend less time managing your data environment, and more time building a data-driven business. As the top-ranked ISV for database management software tools in the world, we help you simplify this complex technology in order to manage, monitor and move your data across a wide variety of on-premises and cloud-based systems.

Amazon ElastiCache allows you to seamlessly set up, run, and scale popular open-Source compatible in-memory data stores in the cloud. Build data-intensive apps or boost the performance of your existing databases by retrieving data from high throughput and low latency in-memory data stores. Amazon ElastiCache is a popular choice for real-time use cases like Caching, Session Stores, Gaming, Geospatial Services, Real-Time Analytics, and Queuing. Amazon ElastiCache offers fully managed Redis and Memcached for your most demanding applications that require sub-millisecond response times. Amazon ElastiCache works as an in-memory data store and cache to support the most demanding applications requiring sub-millisecond response times. By utilizing an end-to-end optimized stack running on customer-dedicated nodes, Amazon ElastiCache provides secure, blazing-fast performance.

Easily deploy applications to the cloud using your choice of languages and frameworks. Achieve business continuity and dynamically respond to changes in customer demand with built-in high availability and elastic scaling. Get unparalleled security and compliance, including Azure IP Advantage, and industry-leading reach through a global network of Microsoft data centers. Choose the right resources for your workloads, with no hidden costs. Combine MariaDB Community edition with the benefits of a fully managed service provider to free developers from complex infrastructure and database management so they can focus on building exceptional apps. Azure Database for MariaDB works with popular open-source frameworks and languages and features tight integration with Azure web apps. Use it with popular content management apps, such as WordPress and Drupal, for a fully integrated experience that supports your specific application development needs.

A high-performance cross-platform historical time-series columnar database featuring: - An in-memory compute engine - A real-time streaming processor - An expressive query and programming language called q

Through its Native Parallel Graph™ technology, the TigerGraph™ graph platform represents what’s next in the graph database evolution: a complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time. Combining the best ideas (MapReduce, Massively Parallel Processing, and fast data compression/decompression) with fresh development, TigerGraph delivers what you’ve been waiting for: the speed, scalability, and deep exploration/querying capability to extract more business value from your data.

Pinot is designed to answer OLAP queries with low latency on immutable data. Pluggable indexing technologies - Sorted Index, Bitmap Index, Inverted Index. Joins are currently not supported, but this problem can be overcome by using Trino or PrestoDB for querying. SQL like language that supports selection, aggregation, filtering, group by, order by, distinct queries on data. Consist of of both offline and real-time table. Use real-time table only to cover segments for which offline data may not be available yet. Detect the right anomalies by customizing anomaly detect flow and notification flow.

Use Azure Table storage to store petabytes of semi-structured data and keep costs down. Unlike many data stores—on-premises or cloud-based—Table storage lets you scale up without having to manually shard your dataset. Availability also isn’t a concern: using geo-redundant storage, stored data is replicated three times within a region—and an additional three times in another region, hundreds of miles away. Table storage is excellent for flexible datasets—web app user data, address books, device information, and other metadata—and lets you build cloud applications without locking down the data model to particular schemas. Because different rows in the same table can have a different structure—for example, order information in one row, and customer information in another—you can evolve your application and table schema without taking it offline. Table storage embraces a strong consistency model.

Use Apache HBase™ when you need random, realtime read/write access to your Big Data. This project's goal is the hosting of very large tables -- billions of rows X millions of columns -- atop clusters of commodity hardware. Automatic failover support between RegionServers. Easy to use Java API for client access. Thrift gateway and a REST-ful Web service that supports XML, Protobuf, and binary data encoding options. Support for exporting metrics via the Hadoop metrics subsystem to files or Ganglia; or via JMX.

A Kudu cluster stores tables that look just like tables you're used to from relational (SQL) databases. A table can be as simple as a binary key and value, or as complex as a few hundred different strongly-typed attributes. Just like SQL, every table has a primary key made up of one or more columns. This might be a single column like a unique user identifier, or a compound key such as a (host, metric, timestamp) tuple for a machine time-series database. Rows can be efficiently read, updated, or deleted by their primary key. Kudu's simple data model makes it a breeze to port legacy applications or build new ones, no need to worry about how to encode your data into binary blobs or make sense of a huge database full of hard-to-interpret JSON. Tables are self-describing, so you can use standard tools like SQL engines or Spark to analyze your data. Kudu's APIs are designed to be easy to use.

Ehcache is an open source, standards-based cache that boosts performance, offloads your database, and simplifies scalability. It's the most widely-used Java-based cache because it's robust, proven, full-featured, and integrates with other popular libraries and frameworks. Ehcache scales from in-process caching, all the way to mixed in-process/out-of-process deployments with terabyte-sized caches. Terracotta actively develops, maintains, and supports Ehcache as a professional open source project available under an Apache 2.0 license. Contributors are welcome to join our community.

Proactively manage all major DBMSs (SQL Server, Azure SQL Database, Oracle Database, Sybase ASE and IQ, Db2 LUW and z/OS, Redshift, MySQL, PostgreSQL, and Greenplum) from a single common interface. Reduce training requirements and streamline collaboration among different teams across the organization. Manage multiple Oracle-specific schema object types and SQL Server advanced object properties such as temporal tables, in-memory tables, and natively compiled triggers, procedures and functions. Comprehensive tools help you manage space, data and performance to keep your databases optimized and available. Manage the performance of your databases with a built-in process monitor that helps you understand who is connected to your database along with each user's current activity and session-related data. Sophisticated diagnostics help you pinpoint performance inefficiencies that result in poor space management, tracking key database metadata and performance metrics over time.

Impala provides low latency and high concurrency for BI/analytic queries on the Hadoop ecosystem, including Iceberg, open data formats, and most cloud storage options. Impala also scales linearly, even in multitenant environments. Impala is integrated with native Hadoop security and Kerberos for authentication, and via the Ranger module, you can ensure that the right users and applications are authorized for the right data. Utilize the same file and data formats and metadata, security, and resource management frameworks as your Hadoop deployment, with no redundant infrastructure or data conversion/duplication. For Apache Hive users, Impala utilizes the same metadata and ODBC driver. Like Hive, Impala supports SQL, so you don't have to worry about reinventing the implementation wheel. With Impala, more users, whether using SQL queries or BI applications, can interact with more data through a single repository and metadata stored from source through analysis.

Kwil is the first decentralized, community-owned SQL database solution for building advanced dApps and protocols. Kwil enables advanced dApp development in a vastly shorter time by providing a highly scalable SQL database that feels native to Web2 developers. In order to build on a decentralized architecture, developers are currently required to manage highly complex and extremely unscalable blockchain-based data management solutions. KwilDB simplifies the decentralized development process while simultaneously providing an extremely cheap and scalable solution for storing and querying large amounts of data. By facilitating highly scalable decentralized data storage and querying, KwilDB enables dApps to seamlessly plug into data from other applications. Building on KwilDB means radically faster development times, the ability to quickly execute highly complex queries across massive data sets, and ease of access to data from other applications, enabling extreme composability.

NCache is an open source distributed cache for .NET Framework & .NET Core (released under Apache License, Version 2.0), by Alachisoft. NCache provides an extremely fast and linearly scalable distributed cache that caches application data and reduces expensive database trips. Organizations use NCache to remove performance bottlenecks related to their data storage and databases and can scale their .NET and Java applications to extreme transaction processing (XTP). NCache Open Source gives the .NET developer community unrestricted access to the industry’s oldest and most popular distributed cache. Due to its Open Source nature .NET developers finally have complete access to a truly elastic .NET distributed cache that fits in nicely with their application’s .NET stack. Alachisoft is the market leader since 2003 through its product NCache. Founded in 1996 as a software development services company, Alachisoft transitioned to a product company in 2003

HSQLDB (HyperSQL DataBase) is the leading SQL relational database system written in Java. It offers a small, fast multithreaded and transactional database engine with in-memory and disk-based tables and supports embedded and server modes. It includes a powerful command line SQL tool and simple GUI query tools. HSQLDB supports the widest range of SQL Standard features seen in any open source database engine: SQL:2016 core language features and an extensive list of SQL:2016 optional features. It supports full Advanced ANSI-92 SQL with only two exceptions. Many extensions to the Standard, including syntax compatibility modes and features of other popular database engines, are also supported.

An open-source, cloud-native, distributed SQL database for elastic scale and real-time analytics. Supported by a wealth of open-source data migration tools in the ecosystem, TiDB gives you the freedom to choose your own vendor and avoid lock-in. Purposely built to deliver SQL at scale, TiDB eliminates the scaling problems of traditional relational databases without intrusion to your application. HTAP database platform that enables real-time situation awareness and decision making on live transactional data and eliminates friction between IT and business goals. TiDB is ACID-compliant and strongly consistent. You can use TiDB as a scale-out MySQL database with familiar SQL syntaxes and ecosystem tools. TiDB automatically shards your data so you don’t have to do it manually. You can simply add new nodes to scale horizontally and elastically to meet your business growth. TiDB simplifies the ETL process and automatically recovers from errors.

GaussDB(for MySQL) is a next generation MySQL-compatible, enterprise-class distributed database service. It uses a decoupled compute and storage architecture and data functions virtualization (DFV) storage that auto-scales up to 128 TB per DB instance. There is virtually no risk of data loss. It supports millions of QPS throughputs and cross-AZ deployment, combining the performance and reliability of commercial databases with the flexibility of open source databases. By decoupling compute and storage, connecting them through RDMA, and using a "log as database" architecture, you can get seven times the performance of open-source databases. To scale read capacity and performance, you can add up to 15 read replicas for a primary node within minutes. GaussDB(for MySQL) is fully compatible with MySQL. You can easily migrate your MySQL databases to GaussDB(for MySQL) without reconstructing existing applications and without sharding.