As of May 2026, there are 13 SaaS companies in Key Value Databases. They have combined revenues of $1.1B and employ 7.4K people. They have raised $811.2M and serve 500 customers combined.
Key-value databases are a type of non-relational database, commonly categorized under NoSQL databases, that store data as a collection of key-value pairs. This structure provides a simple and efficient way to access and manipulate data, making these databases particularly suited for scenarios requiring high-speed transactions and scalability. They are widely used in applications such as caching, session storage, and real-time analytics, where quick retrieval and storage of data is paramount. Typical features of key-value databases include high availability, partitioning, and various data expiration policies. They often support horizontal scaling, allowing them to handle increased loads seamlessly. Common buyer personas for key-value databases include software developers and data engineers, who seek to implement flexible and scalable data solutions, as well as IT operations teams focused on maintaining performance and availability in dynamic environments.
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Showing 10 of 4 companies ranked by annual revenue.
Mountain View, California, United States
Redis Ltd. (originally Redis Labs, Garantia Data) is an American private computer software company headquartered in Mountain View, California. It is the world's fastest in-memory database, providing cloud and on-prem solutions for caching, vector search, and NoSQL databases.
Wilmington, Delaware, United States
The Apache Software Foundation (ASF) is the global home for open source software, powering some of the world’s most ubiquitous software projects including Apache Airflow, Apache Camel, Apache Cassandra, Apache Groovy, Apache HTTP Server, and Apache Kafka. Established in 1999, The ASF is at the forefront of open source innovation, setting industry standards to advance software for the public good. We sustain open source projects in perpetuity, empowering developers to build communities that endure. Everything we do is open. Everyone is welcome. Learn more at https://apache.org. ASF’s annual Community Over Code event is where open source technologists convene to share best practices and use cases, forge critical relationships, and learn about advancements in their field. https://communityovercode.org/
Santa Clara, California, United States
The company that owns datastax.com is DataStax, Inc. DataStax is a software company that specializes in delivering an always-on, distributed database platform built on Apache Cassandra. The company was founded in 2010 and is based in Santa Clara, California, with additional offices around the world. DataStax helps businesses unlock the full potential of their data by providing a scalable, highly available, and secure database platform that can handle massive amounts of data and support real-time applications. Their customers include some of the world's largest companies in industries such as finance, healthcare, and retail.
Boston, Massachusetts, United States
InterSystems, a creative data technology provider, delivers a unified foundation for next-generation applications for healthcare, finance, manufacturing, and supply chain customers in more than 80 countries. Our data platforms solve interoperability, speed, and scalability problems for large organizations around the globe to unlock the power of data and allow people to perceive data in imaginative ways. Established in 1978, InterSystems is committed to excellence through its 24×7 support for customers and partners around the world. Privately held and headquartered in Boston, Massachusetts, InterSystems has 39 offices in 28 countries worldwide.
- The product must store data primarily in key-value pairs. - It should support high availability and scalability for large datasets. - The database should allow for quick retrieval and storage of data. - It must include features for data expiration or time-to-live settings. - The system should not be limited to relational data structures; must also support unstructured or semi-structured data.
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