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

Scylladb is a Cassandra compatible NoSQL column store which can do 1MM transactions/sec per server. It scales up linearly with number of cores. 

ScyllaDB - NoSQL Column Store Database compatible with Cassandra

SurrealDB is the ultimate mult--modal database for tomorrow's applications. SurrealDB is an end-to-end cloud-native database designed for modern applications, including web, mobile, serverless, Jamstack, backend, and traditional applications. With SurrealDB, you can simplify your database and API infrastructure, reduce development time, and build secure, performant apps quickly and cost-effectively.
<ul dir="auto">
<li>Reduces development time: SurrealDB simplifies your database and API stack by removing the need for most server-side components, allowing you to build secure, performant apps faster and cheaper.</li>
<li>Real-time collaborative API backend service:&nbsp;SurrealDB functions as both a database and an API backend service, enabling real-time collaboration.</li>
<li>Support for multiple querying languages:&nbsp;SurrealDB supports SQL querying from client devices, GraphQL, ACID transactions, WebSocket connections, structured and unstructured data, graph querying, full-text indexing, and geospatial querying.</li>
<li>Granular access control: SurrealDB provides row-level permissions-based access control, giving you the ability to manage data access with precision.</li>
<li class="task-list-item">Record links and directed typed graph connections</li>
<li>Incrementally computed views for pre-computed advanced analytics</li>
<li>Connect and query directly from web-browsers and client devices</li>
<li>Store and model data in any way with tables, documents, and graph</li>
<li>Simple schema definition for frontend and backend development</li>
<li>Use embedded JavaScript functions for custom advanced functionality</li>
</ul>

SurrealDB is an end-to-end cloud-native database designed for modern applications, including web, mobile, serverless, Jamstack, backend, and traditional applications.

SurrealDB - A scalable, distributed, collaborative, document-graph database, for the realtime web

FlockDB is much simpler than other graph databases such as neo4j because it tries to solve fewer problems. It scales horizontally and is designed for on-line, low-latency, high throughput environments such as web-sites. Twitter uses FlockDB to store social graphs (who follows whom, who blocks whom) and secondary indices. As of April 2010, the Twitter FlockDB cluster stores 13+ billion edges and sustains peak traffic of 20k writes/second and 100k reads/second.

FlockDB - A distributed, fault-tolerant graph database from Twitter

Sensei is a distributed data system that was built to support many product initiatives at LinkedIn, including the real-time faceted search in <A HREF="http://www.linkedin.com/signal/" target="_blank">LinkedIn Signal</A> and the news feed and tabs on the Homepage. Sensei is both a search engine and a database. It is designed to query and navigate through documents that consist of unstructured text and well-formed and structured metadata. 
 It supports Fast realtime updates, Complex query language and REST/JSON api, Hadoop integration and lot more.

Sensei is a distributed data system that was built to support many product initiatives at LinkedIn, including the real-time faceted search in LinkedIn Signal and the news feed and tabs on the Homepage. Sensei is both a search engine and a database. It is designed to query and navigate through documents that consist of unstructured text and  well-formed and structured metadata. Sensei is both a search engine and a database.

SenseiDB - Distributed, Realtime, Semi-Structured Database from LinkedIn

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.

ConcourseDB is a distributed self-tuning database with automatic indexing, version control and ACID transactions. ConcourseDB provides a more intuitive approach to data management that is easy to deploy, access and scale while maintaining the strong consistency of traditional database systems.

ConcourseDB  - Self-tuning database designed for both transactions and ad hoc analytics across time

CurioDB is a distributed and persistent Redis clone, built with Scala and Akka. Please note that despite the fancy logo, this is a toy project, hence the name "Curio", and any suitability as a drop-in replacement for Redis is purely incidental.

CurioDB - Distributed & Persistent Redis Clone built with Scala & Akka

Bangdb is pure vanilla key value nosql data store. The goal of bangdb is to be fast, reliable, robust, scalable and easy to use data store for various data management services required by applications. Bangdb comes in flavors like Embedded In memory, Network, Distributed data grid/ Elastic Cache. The bangdb is highly concurrent and runs parallel operations as much as possible.

BangDB - NoSQL for Real Time Performance

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