The Apache Cassandra Project develops a highly scalable second-generation distributed database, bringing together Dynamo's fully distributed design and Bigtable's ColumnFamily-based data model. Cassandra is suitable for applications that can't afford to lose data. Data is automatically replicated to multiple nodes for fault-tolerance. 

 Cassandra provides support for Scale out, load balancing, cluster growth, Flexible schema, Key-oriented queries and CAP theorem (Consistency, Availability, Partition tolerance). It is in use at Digg, Facebook, Twitter, Reddit, Rackspace, Cloudkick, Cisco and more companies.

The Apache Cassandra Project develops a highly scalable second-generation distributed database, bringing together Dynamo's fully distributed design and Bigtable's ColumnFamily-based data model. Cassandra is suitable for applications that can't afford to lose data. Data is automatically replicated to multiple nodes for fault-tolerance.

Cassandra - Scalable Distributed Database

HBase provides support to handle BigTable - billions of rows X millions of columns. It is a scalable, distributed, versioned, column-oriented store modeled after Google's Bigtable and runs on top of HDFS (Hadoop Distributed Filesystem). It features compression, in-memory operation per-column. Data could be replicated between the nodes. HBase is used in Facebook and Twitter.

HBase -  Hadoop database

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. Large queries are parallelized using multiple cores, taking all the necessary resources available on the current server. It supports distributed processing, data can reside on different shards. Each shard can be a group of replicas used for fault tolerance. All shards are used to run a query in parallel, transparently for the user.
 
ClickHouse implements user account management using SQL queries and allows for role-based access control configuration similar to what can be found in ANSI SQL standard and popular relational database management systems. It uses asynchronous multi-master replication. After being written to any available replica, all the remaining replicas retrieve their copy in the background. It adaptively chooses how to JOIN multiple tables, by preferring hash-join algorithm and falling back to the merge-join algorithm if there’s more than one large table.

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. Large queries are parallelized using multiple cores, taking all the necessary resources available on the current server. It supports distributed processing, data can reside on different shards. Each shard can be a group of replicas used for fault tolerance. All shards are used to run a query in parallel, transparently for the user.

ClickHouse - Column-oriented database management system that allows generating analytical data reports in real time

FoundationDB is a distributed database designed to handle large volumes of structured data across clusters of commodity servers. It organizes data as an ordered key-value store and employs ACID transactions for all operations. It is especially well-suited for read/write workloads but also has excellent performance for write-intensive workloads. Users interact with the database using API language binding.
 
FoundationDB is multi-model, meaning you can store many types data in a single database. All data is safely stored, distributed, and replicated in the Key-Value Store component. It provides amazing performance on commodity hardware, allowing you to support very heavy loads at low cost.

FoundationDB is a distributed database designed to handle large volumes of structured data across clusters of commodity servers. It organizes data as an ordered key-value store and employs ACID transactions for all operations. It is especially well-suited for read/write workloads but also has excellent performance for write-intensive workloads. Users interact with the database using API language binding. 

FoundationDB - Distributed, Transactional Key-value store

Trino is a highly parallel and distributed query engine, that is built from the ground up for efficient, low latency analytics. It is an ANSI SQL compliant query engine, that works with BI tools such as R, Tableau, Power BI, Superset and many others. It helps to 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. For example, join historic log data stored in an S3 object storage with customer data stored in a MySQL relational database.

Trino is a highly parallel and distributed query engine, that is built from the ground up for efficient, low latency analytics. It is an ANSI SQL compliant query engine, that works with BI tools such as R, Tableau, Power BI, Superset and many others. It helps to 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. 

Trino - A query engine that runs at ludicrous speed

Apache Trafodion is a webscale SQL-on-Hadoop solution enabling transactional or operational workloads on Apache Hadoop. Trafodion builds on the scalability, elasticity, and flexibility of Hadoop. Trafodion extends Hadoop to provide guaranteed transactional integrity, enabling new kinds of big data applications to run on Hadoop. 
 
<ul> 
 <li>Full-functioned ANSI SQL language support</li> 
 <li>JDBC/ODBC connectivity for Linux/Windows clients</li> 
 <li>Distributed ACID transaction protection across multiple statements, tables and/or rows</li> 
 <li>Transaction recovery to achieve database consistency</li> 
 <li>Optimization for low-latency read and write transactions</li> 
 <li>Support for large data sets using a parallel-aware query optimizer</li> 
 <li>Performance improvements for OLTP workloads with compile-time and run-time optimizations</li> 
 <li>Distributed parallel-processing architecture designed for scalability</li> 
 </ul>

Apache Trafodion is a webscale SQL-on-Hadoop solution enabling transactional or operational workloads on Apache Hadoop. Trafodion builds on the scalability, elasticity, and flexibility of Hadoop. Trafodion extends Hadoop to provide guaranteed transactional integrity, enabling new kinds of big data applications to run on Hadoop. 

Apache Trafodion - Webscale SQL-on-Hadoop solution enabling transactional or operational workloads on Apache Hadoop. 

A cloud-native database for building mission-critical applications. This repository contains the Community Edition of the YugaByte Database.YugaByte offers both SQL and NoSQL in a single, unified db. It is meant to be a system-of-record/authoritative database that applications can rely on for correctness and availability. It allows applications to easily scale up and scale down in the cloud, on-premises or across hybrid environments without creating operational complexity or increasing the risk of outages.
 
YugaByte DB is world's only distributed database that is both non-relational (supports Redis-compatible key-value & Cassandra-compatible flexible schema APIs) and relational (PostgreSQL-compatible distributed SQL API) at the same time. It is purpose-built to power fast-growing online services on public, private and hybrid clouds with transactional integrity, low latency, high throughput and multi-region scalability while also providing unparalleled data modeling freedom to application architects.

A cloud-native database for building mission-critical applications. This repository contains the Community Edition of the YugaByte Database.YugaByte offers both SQL and NoSQL in a single, unified db. It is meant to be a system-of-record/authoritative database that applications can rely on for correctness and availability. It allows applications to easily scale up and scale down in the cloud, on-premises or across hybrid environments without creating operational complexity or increasing the risk of outages.

YugaByte Database - Transactional, high-performance database for building internet-scale, globally-distributed applications

Apache ShardingSphere is an open-source ecosystem consisted of a set of distributed database solutions, including 3 independent products, JDBC, Proxy & Sidecar (Planning). They all provide functions of data scale-out, distributed transaction and distributed governance, applicable in a variety of situations such as Java isomorphism, heterogeneous language and cloud-native.
 
Features: 
<ul>
<li>Database sharding &amp; Table sharding</li>
<li>Replica query</li>
<li>Sharding strategy customization</li>
<li>Centre-less Distributed primary key</li>
<li>Distributed Governance</li>
<li>Data migration &amp; Scale-out</li>
<li>Observability(Tracing/Metrics) Supported</li>
<li>Data Encryption&amp;Decryption</li>
<li>Shadow Table for Performance Testing</li>
<li>Unified Transaction API</li>
</ul>

Apache ShardingSphere is an open-source ecosystem consisted of a set of distributed database solutions, including 3 independent products, JDBC, Proxy & Sidecar (Planning). They all provide functions of data scale-out, distributed transaction and distributed governance, applicable in a variety of situations such as Java isomorphism, heterogeneous language and cloud-native.

Apache ShardingSphere - Distributed Database Ecosphere 

OmniSciDB is the foundation of the OmniSci platform. OmniSciDB is SQL-based, relational, columnar and specifically developed to harness the massive parallelism of modern CPU and GPU hardware. OmniSciDB can query up to billions of rows in milliseconds, and is capable of unprecedented ingestion speeds, making it the ideal SQL engine for the era of big, high-velocity data.
 
OmniSciDB optimizes the memory and compute layers to deliver unprecedented performance. OmniSciDB was designed to keep hot data in GPU memory for the fastest access possible. Other GPU database systems have taken the approach of storing the data in CPU memory, only moving it to GPU at query time, trading the gains they receive from GPU parallelism with transfer overheads over the PCIe bus.
 
OmniSciDB natively supports standard SQL and returns query results hundreds of times faster than CPU-only analytical database platforms. Analysts and data scientists can still rely on their existing SQL knowledge, querying data using industry-standard SQL.

OmniSciDB is the foundation of the OmniSci platform. OmniSciDB is SQL-based, relational, columnar and specifically developed to harness the massive parallelism of modern CPU and GPU hardware. OmniSciDB can query up to billions of rows in milliseconds, and is capable of unprecedented ingestion speeds, making it the ideal SQL engine for the era of big, high-velocity data.

OmniSciDB - Open Source Analytical Database & SQL Engine

CockroachDB is a cloud-native SQL database for building global, scalable cloud services that survive disasters.CockroachDB is a distributed SQL database built on a transactional and strongly-consistent key-value store. It scales horizontally; survives disk, machine, rack, and even datacenter failures with minimal latency disruption and no manual intervention; supports strongly-consistent ACID transactions; and provides a familiar SQL API for structuring, manipulating, and querying data.
 
CockroachDB supports the PostgreSQL wire protocol, so you can use any available PostgreSQL client drivers.

CockroachDB is a cloud-native SQL database for building global, scalable cloud services that survive disasters.CockroachDB is a distributed SQL database built on a transactional and strongly-consistent key-value store. It scales horizontally; survives disk, machine, rack, and even datacenter failures with minimal latency disruption and no manual intervention; supports strongly-consistent ACID transactions; and provides a familiar SQL API for structuring, manipulating, and querying data.

CockroachDB - Cloud-native SQL database.

LinDB is an open-source Time Series Database which provides high performance, high availability and horizontal scalability. LinDB takes a lot of best practice of TSDB and implements some optimizations based on the characteristics of time series data. Unlike writing a lot of Continuous-Query for InfluxDB, LinDB supports rollup in specific interval automatically after creating the database. Moreover, LinDB is extremely fast for parallel querying and computing of distributed time series data.
 
LinDB supports Metric + Tags + Fields, and is schema-free; The LinQL is handy for realtime data analytics. Tags based sharding strategy in LinDB solves the hotspots problem, and is truly horizontally expanded available by simply adding new broker and storage nodes.

LinDB is an open-source Time Series Database which provides high performance, high availability and horizontal scalability. LinDB takes a lot of best practice of TSDB and implements some optimizations based on the characteristics of time series data. Unlike writing a lot of Continuous-Query for InfluxDB, LinDB supports rollup in specific interval automatically after creating the database. Moreover, LinDB is extremely fast for parallel querying and computing of distributed time series data.


Lindb - Distributed Time Series Database

Nebula Graph is an open-source graph database capable of hosting super large-scale graphs with billions of vertices (nodes) and trillions of edges, with milliseconds of latency. It delivers enterprise-grade high performance to simplify the most complex data sets imaginable into meaningful and useful information. 
 
Nebula Graph is Symmetrically distributed, Separates Storage and computation, Horizontal scalability, Strong data consistency by RAFT protocol, Role-based access control for higher level security and lot more.

Nebula Graph is an open-source graph database capable of hosting super large-scale graphs with billions of vertices (nodes) and trillions of edges, with milliseconds of latency. It delivers enterprise-grade high performance to simplify the most complex data sets imaginable into meaningful and useful information. 

Nebula Graph - A distributed, scalable, lightning-fast graph database

Cloudata is Distributed Large scale Structured Data Storage, and open source project implementing Google's Bigtable. It's DBMS(Database Management System), but not Relational DBMS. It can store more than Peta bytes.

Cloudata - Structured Data Storage implementing Google's Bigtable.

PolarDB for PostgreSQL (PolarDB for short) is an open-source database system based on PostgreSQL. It extends PostgreSQL to become a share-nothing distributed database, which supports global data consistency and ACID across database nodes, distributed SQL processing, and data redundancy and high availability through Paxos based replication. PolarDB is designed to add values and new features to PostgreSQL in dimensions of high performance, scalability, high availability, and elasticity. At the same time, PolarDB remains SQL compatibility to standalone PostgreSQL with the best effort.
 
PolarDB will evolve and offer its functions and features in two major parts: an extension and a patch to PostgreSQL. The extension part includes components implemented outside the PostgreSQL kernel, such as distributed transaction management, global or distributed time service, distributed SQL processing, additional metadata, internal functions, and tools to manage database clusters and conduct fault tolerance or recovery. Having most of its functions in a PostgreSQL extension, PolarDB targets easy upgrading, easy migration, and fast adoption. The patch part includes the changes necessary to the kernel, such as distributed MVCC for different isolation levels. We expect functions and codes in the patch part is limited. As a result, PolarDB can be easily upgraded with newer PostgreSQL versions and maintained full compatibility with PostgreSQL.

PolarDB for PostgreSQL (PolarDB for short) is an open-source database system based on PostgreSQL. It extends PostgreSQL to become a share-nothing distributed database, which supports global data consistency and ACID across database nodes, distributed SQL processing, and data redundancy and high availability through Paxos based replication.

PolarDB - Share-nothing, Distributed database based on PostgreSQL

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