Alternatives to Greenplum

ANSI SQL allows you to analyze petabytes worth of data at lightning-fast speeds with no operational overhead. Analytics at scale with 26%-34% less three-year TCO than cloud-based data warehouse alternatives. You can unleash your insights with a trusted platform that is more secure and scales with you. Multi-cloud analytics solutions that allow you to gain insights from all types of data. You can query streaming data in real-time and get the most current information about all your business processes. Machine learning is built-in and allows you to predict business outcomes quickly without having to move data. With just a few clicks, you can securely access and share the analytical insights within your organization. Easy creation of stunning dashboards and reports using popular business intelligence tools right out of the box. BigQuery's strong security, governance, and reliability controls ensure high availability and a 99.9% uptime SLA. Encrypt your data by default and with customer-managed encryption keys

Amazon Redshift is preferred by more customers than any other cloud data storage. Redshift powers analytic workloads for Fortune 500 companies and startups, as well as everything in between. Redshift has helped Lyft grow from a startup to multi-billion-dollar enterprises. It's easier than any other data warehouse to gain new insights from all of your data. Redshift allows you to query petabytes (or more) of structured and semi-structured information across your operational database, data warehouse, and data lake using standard SQL. Redshift allows you to save your queries to your S3 database using open formats such as Apache Parquet. This allows you to further analyze other analytics services like Amazon EMR and Amazon Athena. Redshift is the fastest cloud data warehouse in the world and it gets faster each year. The new RA3 instances can be used for performance-intensive workloads to achieve up to 3x the performance compared to any cloud data warehouse.

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.

StarTree Cloud is a fully-managed user-facing real-time analytics Database-as-a-Service (DBaaS) designed for OLAP at massive speed and scale. 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. 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.

Searching and analyzing structured data is easy; however, over 80% of generated data is unstructured, requiring a different approach. Machine learning converts unstructured data into high-dimensional vectors of numerical values, which makes it possible to find patterns or relationships within that data type. Unfortunately, traditional databases were never meant to store vectors or embeddings and can not meet unstructured data's scalability and performance requirements. Zilliz Cloud is a cloud-native vector database that stores, indexes, and searches for billions of embedding vectors to power enterprise-grade similarity search, recommender systems, anomaly detection, and more. Zilliz Cloud, built on the popular open-source vector database Milvus, allows for easy integration with vectorizers from OpenAI, Cohere, HuggingFace, and other popular models. Purpose-built to solve the challenge of managing billions of embeddings, Zilliz Cloud makes it easy to build applications for scale.

ClickHouse is an open-source OLAP database management software that is fast and easy to use. It is column-oriented, and can generate real-time analytical reports by using SQL queries. ClickHouse's performance is superior to comparable column-oriented database management software currently on the market. It processes hundreds of millions of rows to more than a million and tens if not thousands of gigabytes per second. ClickHouse makes use of all hardware available to process every query as quickly as possible. Peak processing speed for a single query is more than 2 Terabytes per Second (after decompression, only utilized columns). To reduce latency, reads in distributed setups are automatically balanced between healthy replicas. ClickHouse supports multimaster asynchronous replication, and can be deployed across multiple datacenters. Each node is equal, which prevents single points of failure.

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.

The Open, Multi-Cloud Stack to Modern Data Apps. Built on Apache Cassandra™, an open-source Apache Cassandra™. Global scale and 100% uptime without vendor lock in You can deploy on multi-clouds, open-source, on-prem and Kubernetes. For a lower TCO, use elastic and pay-as you-go. Stargate APIs allow you to build faster with NoSQL, reactive, JSON and REST. Avoid the complexity of multiple OSS projects or APIs that don’t scale. It is ideal for commerce, mobile and AI/ML. Get building modern data applications with Astra, a database-as-a-service powered by Apache Cassandra™. Richly interactive apps that are viral-ready and elastic using REST, GraphQL and JSON. Pay-as you-go Apache Cassandra DBaaS which scales easily and affordably

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

Apache Druid, an open-source distributed data store, is Apache Druid. Druid's core design blends ideas from data warehouses and timeseries databases to create a high-performance real-time analytics database that can be used for a wide range of purposes. Druid combines key characteristics from each of these systems into its ingestion, storage format, querying, and core architecture. Druid compresses and stores each column separately, so it only needs to read the ones that are needed for a specific query. This allows for fast scans, ranking, groupBys, and groupBys. Druid creates indexes that are inverted for string values to allow for fast search and filter. Connectors out-of-the box for Apache Kafka and HDFS, AWS S3, stream processors, and many more. Druid intelligently divides data based upon time. Time-based queries are much faster than traditional databases. Druid automatically balances servers as you add or remove servers. Fault-tolerant architecture allows for server failures to be avoided.

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.

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.

We make BI and Big Data analytics easier and more efficient. Our goal is to empower business users, make BI specialists and always-busy business more independent when solving data-driven business problems. Querona is a solution for those who have ever been frustrated by a lack in data, slow or tedious report generation, or a long queue to their BI specialist. Querona has a built-in Big Data engine that can handle increasing data volumes. Repeatable queries can be stored and calculated in advance. Querona automatically suggests improvements to queries, making optimization easier. Querona empowers data scientists and business analysts by giving them self-service. They can quickly create and prototype data models, add data sources, optimize queries, and dig into raw data. It is possible to use less IT. Users can now access live data regardless of where it is stored. Querona can cache data if databases are too busy to query live.

Choose from a wide range of SQL features to realise your applications from pure analytics to hybrid transactional/analytical processing. MonetDB returns queries in seconds, if not faster, when you are curious about your data and when you need to work efficiently. You can (re)use your code when you need specialised function: Use the hooks to add your user-defined functions to SQL, Python R, C/C++, or R. Join us to expand the MonetDB community that spans 130+ countries. We have students, teachers, researchers and small businesses. Join the most important Database in Analytical Jobs to surf the innovation! MonetDB's simple setup will quickly get your DBMS up to speed.

The Apache Cassandra database provides high availability and scalability without compromising performance. It is the ideal platform for mission-critical data because it offers linear scalability and demonstrated fault-tolerance with commodity hardware and cloud infrastructure. Cassandra's ability to replicate across multiple datacenters is first-in-class. This provides lower latency for your users, and the peace-of-mind that you can withstand regional outages.

Hypertable provides scalable database capacity at maximum speed to speed up big data applications and reduce your hardware footprint. Hypertable offers superior performance and efficiency over other competitors, which can translate into significant cost savings. It is a proven, scalable design that powers hundreds Google services. Open source brings all the benefits of open-source with a vibrant community. C++ implementation for optimal performance. Support for your business-critical big-data application is available 24/7/365 The employer of all core Hypertable developers provides unrivalled access to the Hypertable brain power. Hypertable was created to solve the scalability issue. This problem is not well handled by traditional RDBMSs. Hypertable is a Google-developed design that meets their scalability requirements. It solves the scale problem better then any other NoSQL solutions.

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.

QikkDB is an GPU-accelerated columnar database that delivers outstanding performance for complex polygon operations as well as big data analytics. qikkDB is the best choice if you want to count your data in billions, and see real-time results. We are compatible with both Windows and Linux operating systems. Google Tests is our testing framework. The project contains hundreds of unit and tens integration tests. Microsoft Visual Studio 2019 is recommended for Windows development. Its dependencies include CUDA version 10.2 minimum, CMake 3.15 and newer, vcpkg., boost. The dependencies for Linux development are CUDA version 10.2 minimum, CMake 3.15 and newer, boost, and vcpkg. This project is licensed under Version 2.0 of the Apache License. To install qikkDB, you can use an installation script (or dockerfile).

Sadas Engine is the fastest columnar database management system in cloud and on-premise. Sadas Engine is the solution that you are looking for. * Store * Manage * Analyze It takes a lot of data to find the right solution. * BI * DWH * Data Analytics The fastest columnar Database Management System can turn data into information. It is 100 times faster than transactional DBMSs, and can perform searches on large amounts of data for a period that lasts longer than 10 years.

DBHawk enabled our customers to comply with GDPR and HIPAA, SOX and GLBA regulations. Self-Service BI & Adhoc Reporting Tool that allows you to set Data Access Policy, connect to multiple data sources, create powerful SQL charts, and dashboards. DBHawk SQL editor allows users to create, edit, and run SQL queries via a web-based interface. DBHawk Query Maker is compatible with all major databases, including Oracle, Microsoft SQL Server and PostgreSQL. A web-based central tool allows you to automate SQL tasks and batch jobs. Our all-in-one data platform provides secure access to SQL, NoSQL, and Cloud databases. Our customers trust us to protect their data and allow them to access it. Centralized Security, Auditing, and insights into your user's activities.

GeoSpock DB - The space-time analytics database - allows data fusion in the connected world. GeoSpockDB is a unique cloud-native database that can be used to query for real-world applications. It can combine multiple sources of Internet of Things data to unlock their full potential, while simultaneously reducing complexity, cost, and complexity. GeoSpock DB enables data fusion and efficient storage. It also allows you to run ANSI SQL query and connect to analytics tools using JDBC/ODBC connectors. Users can perform analysis and share insights with familiar toolsets. This includes support for common BI tools such as Tableau™, Amazon QuickSight™, and Microsoft Power BI™, as well as Data Science and Machine Learning environments (including Python Notebooks or Apache Spark). The database can be integrated with internal applications as well as web services, including compatibility with open-source visualisation libraries like Cesium.js and Kepler.

Your cloud data platform. Access to any data you need with unlimited scalability. All your data is available to you, with the near-infinite performance and concurrency required by your organization. You can seamlessly share and consume shared data across your organization to collaborate and solve your most difficult business problems. You can increase productivity and reduce time to value by collaborating with data professionals to quickly deliver integrated data solutions from any location in your organization. Our technology partners and system integrators can help you deploy Snowflake to your success, no matter if you are moving data into Snowflake.

InfiniDB is a column-store DBMS that is optimized for OLAP workloads. It supports Massive Paralllel Processing (MPP) thanks to its distributed architecture. It uses MySQL as its front end so that MySQL-savvy users can migrate to InfiniDB quickly. Users can connect to InfiniDB with any MySQL connector. InfiniDB applies MVCC to do concurrency control. It uses the term System Change Number (SCN), to indicate a particular version of the system. It uses three structures in its Block Resolution Manager (BRM), version buffer, version substitution, and version buffer block manger, 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. InfiniDB applies range partitioning to each column and stores the minimum and maximal values of each partition in a small structure called an extent map.

Directus is an Open Data Platform that allows you to manage any SQL database's content. It offers a powerful API layer to developers and an intuitive app for non-technical users. Directus is written entirely in JavaScript (primarily Node.js or Vue.js), and it is modular and extensible. This allows it to be tailored to your specific project needs. Our platform can be used to manage digital experiences as a headless CMS, a database client for democratizing information, or as a standalone web app for back-office CRM, inventory, business intelligence and project management.

PolarDB-X was tested at the Tmall Double 11 shopping festival. It has helped customers in a variety of industries, including finance, logistics, energy and public service, to address business problems. Linearly increases storage space to provide petabyte scale storage. This eliminates storage bottlenecks in standalone databases. Massively parallel processing (MPP), which allows for complex analysis and queries on large amounts of data to be significantly improved. It provides extensive algorithms to distribute data across multiple storage devices, effectively reducing the amount of data stored in one table.

Hydra is a column-oriented Postgres that is open source. No code changes required to query billions of rows. Hydra parallelizes, vectorizes, and aggregates (COUNTS, SUMs, AVGs) to deliver the speed that you've always desired on Postgres. Boost performance in every size! Hydra can be installed in just 5 minutes, without requiring any changes to your tools, extensions, syntax, data model or data model. Hydra Cloud allows for smooth sailing and fully managed operations. Different industries have different requirements. Take control of your analytics with powerful Postgres custom functions and extensions. Built by you for you. Hydra is the fastest Postgres on the market. Boost performance by using columnar storage, query parallelization, and vectorization.

Trino is an engine that runs at incredible speeds. Fast-distributed SQL engine for big data analytics. Helps you explore the data universe. Trino is an extremely parallel and distributed query-engine, which is built from scratch for efficient, low latency analytics. Trino is used by the largest organizations to query data lakes with exabytes of data and massive data warehouses. Supports a wide range of use cases including interactive ad-hoc analysis, large batch queries that take hours to complete, and high volume apps that execute sub-second queries. Trino is a ANSI SQL query engine that works with BI Tools such as R Tableau Power BI Superset and many others. You can natively search data in Hadoop S3, Cassandra MySQL and many other systems without having to use complex, slow and error-prone copying processes. Access data from multiple systems in a single query.

Fujitsu Enterprise Postgres, a highly reliable and robust relational database designed for organizations that need high query performance and high availability, is a great choice. It is built on the well-respected open-source PostgreSQL system, and includes enterprise-grade features that enhance security and performance. Fujitsu Enterprise Postgres is managed and installed by Fujitsu's database specialists. They can also help with data migration from your existing database. FEP, which is based on PostgreSQL has high compatibility with other systems and applications. The graphic user interface is simple and clean, which makes it easier for DBAs to execute core database functions such as scanning, queries, and back-up. This makes your data and reports more accessible.

HeatWave, a massively parallel and high-performance, in-memory query accelerator, for Oracle MySQL Database Service, accelerates MySQL performance by orders for analytics and mixed workloads. HeatWave is 6.5X faster that Amazon Redshift at half-the cost, 7X faster then Snowflake at one fifth the cost, and 1400X quicker than Amazon Aurora at half-the cost. MySQL Database Service with HeatWave allows customers to run OLTP or OLAP workloads directly in their MySQL database. This eliminates the need to move and integrate complex, time-consuming and expensive data with separate analytics databases. The new MySQL Autopilot uses machine-learning techniques to automate HeatWave. This makes it easier to use and further increases performance and scalability. HeatWave has been optimized for Oracle Cloud Infrastructure (OCI).

You can view and download the query and session history in the command centre, which also allows you to monitor and manage Greenplum DBMS. Yandex Managed Services for Greenplum®, which includes Hybrid Storage, is natively integrated with Object Storage. This allows you to organize hybrid data storage with automatic transfers to cold storage. In just a few moments, you can deploy a cluster that is ready to use. The DB settings can be changed if needed. Using the DataLens BI integration, you can create reports, charts and dashboards directly from the service based on the data stored in Greenplum. All DBMS connection are encrypted with the TLS protocol. Our infrastructure meets all local regulatory, GDPR and industry-specific ISO standards as well as PCI DSS security requirements.

The fastest NoSQL database in the world. The fastest NoSQL database available, capable of millions IOPS per node with less than 1 millisecond latency. This database will accelerate your application performance. Scylla, a drop-in Apache Cassandra and Amazon DynamoDB alternative, powers your applications with extreme throughput and ultra-low latency. To power modern, high-performance applications, we used the best features of high availability databases to create a NoSQL database that is significantly more efficient, fault-tolerant, and resource-efficient. This high-availability database is built from scratch in C++ for Linux. Scylla unleashes your infrastructure's true potential for running high-throughput/low-latency workloads.

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.

FairCom DB is ideal to handle large-scale, mission critical core-business applications that demand performance, reliability, and scalability that cannot easily be achieved with other databases. FairCom DB provides predictable high-velocity transactions with big data analytics and massively parallel big-data processing. It provides developers with NoSQL APIs that allow them to process binary data at machine speed. ANSI SQL allows for simple queries and analysis over the same binary data. Verizon is one of the companies that has taken advantage of FairCom DB's flexibility. Verizon recently selected FairCom DB to be its in-memory database for the Verizon Intelligent Network Control Platform Transaction Server Migrating. FairCom DB, an advanced database engine, gives you a Continuum of Control that allows you to achieve unparalleled performance at a low total cost of ownership (TCO). FairCom DB doesn't conform to you. FairCom DB conforms. FairCom DB doesn't force you to conform to the database's limitations.

Quest Database Management Solutions. Database technology today is becoming more complex and supporting previously unimaginable data volumes. This is all due to the demands of today’s constantly-on economy. Most organizations spend 65% of their time keeping the lights on. This leaves very little time to innovate and move the business forward. IT must be committed to digital transformation initiatives like cloud migration, DevOps and open-source database adoption. This is at a time when IT is already under great pressure to maintain high service levels. It is time to adopt a new approach. Spend less time managing your data environment and more time building a data-driven company. We are the best-ranked ISV for database management tools in the world. We help you simplify complex technology to manage, monitor, and move your data across many different cloud-based and on-premise systems.

Amazon ElastiCache makes it easy to create, manage, and scale popular open source compatible in-memory cloud data stores. You can build data-intensive apps and improve the performance of existing databases by retrieving data in high-throughput and low latency, in-memory storages. Amazon ElastiCache is popular for real-time applications such as Caching, Session Stores and Gaming, Geospatial Service, Real-Time Analytics and Queuing. Amazon ElastiCache provides fully managed Redis, Memcached and other services for demanding applications that need sub-millisecond response time. Amazon ElastiCache is an in-memory cache and data store that can support the most demanding applications that require sub-millisecond response time. Amazon ElastiCache delivers secure, lightning fast performance by using an optimized stack that runs on customer-dedicated nodes.

High-performance, cross-platform columnar historical time-series columnar data featuring: - An in-memory computation engine - A streaming processor that streams real-time - A combination of a programming language and expressive query, q

Easy deployment of applications to the cloud with your choice in languages and frameworks. High availability and elastic scaling are built-in features that help you achieve business continuity and respond dynamically to changes in customer demands. Azure IP Advantage provides unparalleled security and compliance. The global network of Microsoft's data centers also offers industry-leading reach. No hidden costs. Choose the right resources to meet your workloads. Combining MariaDB Community Edition with the benefits of an entirely managed service provider will free developers from complex database management and infrastructure so they can concentrate on building exceptional applications. Azure Database for MariaDB integrates tightly with Azure web applications and works with popular open source frameworks and languages. Use it with popular content-management apps, such as WordPress or Drupal, to get a fully integrated solution that supports your application development needs.

The TigerGraph™, a graph platform based on its Native Parallel Graph™, technology, represents the next evolution in graph database evolution. It is a complete, distributed parallel graph computing platform that supports 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.

What is Presto? Presto is a distributed, federated SQL query engine that runs on multiple machines. It allows interactive, ad-hoc analysis on large quantities of data. You can run Presto SQL queries against your data. PrestoDB allows you to query data wherever it is located, including Hive and AWS S3, Hadoop and Cassandra, as well as relational databases, NoSQL database, or proprietary data stores. Presto is an open-source engine that allows users to access multiple sources of data, allowing them to perform analytics across the entire organization. A complete Presto installation requires a coordinator and multiple workers. Queries are sent from clients such as the Presto client to the coordinator. The coordinator analyzes, plans, and executes Presto queries.

Azure Table storage can store petabytes semi-structured data at low costs and keeps costs down. Table storage is able to scale up, unlike many cloud-based or on-premise data stores. Also, availability is not a concern. With geo-redundant storage, data can be replicated three times within one region and three times in another region hundreds of miles away. Flexible data such as web app user data, address books, device data and other metadata can be stored in table storage. You can also use table storage to build cloud applications without having to lock down the data model to specific schemas. Different rows can have different structures in the same table, so you can easily change your application and table schema without having to take it offline. Table storage embraces a strong consistency model.

Pinot is designed to answer OLAP questions with low latency and immutable data. Pluggable indexing technologies: Sorted Index (Bitmap Index), Inverted Index. Trino and PrestoDB are both available for querying, but joins are not currently supported. SQL-like language that supports selection and aggregation, filtering as well as group by, order, and distinct queries on data. Both an offline and a real-time table are possible. Only use real-time table to cover segments where offline data is not yet available. Customize anomaly detection flow and notification flow to detect the right anomalies.

Kudu clusters store tables that look exactly like the tables in relational (SQL), databases. A table can have a single binary key and value or a multitude of strongly-typed attributes. Every table has a primary key that is made up of one or more columns, just like SQL. This could be a single column, such as a unique user ID, or a compound key, such as a (host.metric.timestamp) tuple to a machine-time-series database. Rows can be easily read, updated, and deleted by their primary keys. Kudu's data model is simple and easy to use. It makes it easy to port legacy applications and build new ones. You can use standard tools such as Spark or SQL engines to analyze your tables. Tables are self-describing. Kudu's APIs were designed to be simple to use.

Apache HBase™, is used when you need random, real-time read/write access for your Big Data. This project aims to host very large tables, billions of rows and X million columns, on top of clusters of commodity hardware.

Ehcache, an open-source, standards-based cache, boosts performance, offloads your databases, and simplifies scaling. It is the most popular Java-based cache. It is robust, reliable, fully-featured and integrates well with other 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 and maintains Ehcache under an Apache 2.0 license. We welcome contributors to our community.

All major DBMSs (SQL server, Azure SQL Database and Oracle Database, Sybase ASE, IQ, Db2 LUW, and z/OS) can be managed from a single interface. It reduces training time and facilitates collaboration between different teams within the organization. Multiple Oracle-specific schema object types can be managed, as well as advanced SQL Server object properties like temporal tables, in memory tables, natively compiled triggers and procedures, and functions. Comprehensive tools allow you to manage space, data, and performance to keep your database's availability optimized. A built-in process monitor helps you manage the performance of your database. It shows who is connected to your database, as well as current activity and session-related information. Advanced diagnostics can help you identify performance inefficiencies, track key database metadata, and monitor performance metrics over time.

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.

Kwil is the first community-owned, decentralized SQL database solution for building advanced dApps. Kwil enables advanced dApp creation in a significantly shorter time frame by providing a highly scalable SQL data base that feels natural to Web2 developers. Developers are required to manage complex and unscalable blockchain-based data management systems in order to build on a distributed architecture. KwilDB simplifies decentralized development while simultaneously offering a cost-effective and scalable solution to store and query large amounts of data. KwilDB allows dApps to seamlessly connect to data from other applications by allowing for highly scalable, decentralized data storage and querying. KwilDB allows for radically faster development, the ability to execute complex queries across large data sets quickly, and easy access to data from other apps, which results in extreme composability.

Open-source, cloud-native distributed SQL database that allows for elastic scale and real time analytics. TiDB is supported by a wealth open-source data migration tools within the ecosystem. This allows you to choose your own vendor without worrying about lock-in. TiDB was designed to scale SQL without compromising your application. HTAP database platform which enables real-time situation analysis and decision making on transactional data. It eliminates friction between IT goals and business goals. TiDB is ACID compliant and strongly consistent. TiDB can be used as a scaled-out MySQL database using familiar SQL syntaxes. TiDB automatically shards data so you don’t have to do this manually. To scale horizontally or elastically to support your business growth, you can add new nodes. TiDB automates the ETL process, and automatically recovers from errors.

HSQLDB (HyperSQL DataBase), is the most popular SQL relational database system in Java. It is a small, fast, multithreaded, transactional database engine that supports both embedded and server modes. It also includes simple GUI query tools and a powerful command-line SQL tool. HSQLDB supports all the SQL Standard features found in an open-source database engine, including the SQL:2016 core language features as well as a wide range of optional SQL:2016 features. With only two exceptions, it supports Advanced ANSI-92 SQL. Many extensions to the Standard are supported, including syntax compatibility modes, and features of popular database engines.

GaussDB (for MySQL) is a next-generation, enterprise-class distributed database service that is MySQL-compatible. It utilizes a decoupled storage and compute architecture, and data functions virtualization storage (DFV), which auto-scales to 128 TB per DB instances. There is virtually zero risk of data loss. It can support millions of QPS throughputs, cross-AZ deployment, and combines the reliability and performance of commercial databases with open source databases. You can achieve seven times the performance of open source databases by decoupling compute from storage, connecting them via RDMA, using a "log-as-database" architecture, and getting seven times as much performance. You can add up to 15 replicas per primary node in minutes to increase read capacity and performance. GaussDB (for MySQL) is fully compatible. You can migrate your MySQL databases to GaussDB (for MySQL) easily without having to rebuild existing applications or sharding.