As of May 2026, there are 13 SaaS companies in NoSQL Databases. They have combined revenues of $952M and employ 4.1K people. They have raised $1.9B and serve 10K customers combined.
NoSQL databases represent a category of database management systems designed to handle large volumes of unstructured and semi-structured data. Unlike traditional SQL databases, NoSQL solutions offer flexible data models, enabling users to store and retrieve data in various formats, such as key-value pairs, documents, column-family, or graphs. This flexibility makes them particularly suited for real-time analytics, content management, and applications requiring high scalability and performance. The primary use cases for NoSQL databases include managing big data, facilitating high-velocity data ingestion, and supporting applications in industries such as e-commerce, finance, healthcare, and social media. Common features of NoSQL databases include horizontal scaling, schema-less data storage, and support for distributed computing. Users typically include IT professionals, data analysts, and developers who seek to implement systems that can efficiently adapt to changing data requirements and support complex query operations. Organizations adopting NoSQL technology often require solutions that can manage a mix of structured and unstructured data, integrate seamlessly with existing architectures, and scale dynamically based on user demand. As companies increasingly focus on harnessing data for insights and operational efficiencies, NoSQL databases have become an essential component of modern data architecture.
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Showing 10 of 13 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.
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.
Mountain View, California, United States
Redis Labs is a software company that provides a high-performance, in-memory data platform called Redis. The company was founded in 2011 by Ofer Bengal and Yiftach Shoolman and is headquartered in Mountain View, California, with additional offices in Tel Aviv, London, and Bangalore. Redis Labs' platform allows organizations to process and analyze large amounts of data in real-time, enabling faster decision-making and better user experiences. The company's solutions are used by a wide range of industries, including e-commerce, finance, healthcare, and gaming. Redis Labs is recognized as a leader in the NoSQL and in-memory database markets and has won multiple awards for its innovative technology.
San Francisco, California, United States
The core of all AI, business intelligence and applications is data — various bits and bytes that come in all different formats. Only when we sift through this data, reason with it and build on top of it in real time does it give way to vast amounts of information and knowledge. Real-time insights are key to the way we live our lives today; the way we entertain ourselves; the way we listen to music; the way we order groceries. Real-time insights keep your BI tools fresh; they keep your ride-sharing app with the most current price; and they ensure you never miss a fraudulent payment. SingleStoreDB is the world’s only database that empowers users to transact, analyze and contextualize data in real time. It empowers the world’s makers to build, deploy and scale modern, intelligent applications — backed by streaming data ingestion, a unique table type that supports both transactional (OLTP) and analytical (OLAP) workloads, limitless point-in-time recovery and a distributed (shared-nothing), MySQL-compatible architecture.
Mountain View, California, United States
Provides database server so companies can compile and analyze large amounts of data
Shenzhen, Guangdong, China
Developer of database software designed to offer distributed database access for enterprises. The company's software helps enterprises securely store large amounts of transaction data and create data centers, enabling enterprises to improve their data storage and retrieval abilities.
Redwood City, California, United States
Developer of AI-oriented intelligent data processing platform intended to improve query performance. The company's OLAP database systems are based on GPU hardware acceleration which focuses on multiple fields including finance, telecommunications, healthcare and retail, enabling its customers to reduce hardware, operation and maintenance cost by over 10 times.
Palo Alto, California, United States
Provider of an open source in-memory data grid platform designed to modernize existing applications. The company's open source in-memory data grid platform with installed clusters offer operational in-memory computing, enabling companies to manage their data and distribute processing using in-memory storage and parallel execution for breakthrough application speed and scale.
Warsaw, Mazowieckie, Poland
Oxla provides a database that specializes in lightning data processing, offering a distributed database platform capable of processing and handling large, complex queries with ease, designed to be compatible with PostgreSQL and optimized for modern hardware.
San Francisco, California, United States
SurrealDB is an innovative, multi-model, cloud-ready database, suitable for modern and traditional applications. Its versatility, and focus on developer experience, along with the ability for deployment on cloud, on-premise, embedded, and in edge computing environments, allows developers and organisations to meet the needs of their applications, without needing to worry about scalability or keeping data consistent across multiple different database platforms.
- The product must support various data models such as key-value, document, column-family, or graph. - Must provide capabilities for real-time data processing and analytics. - Should enable horizontal scaling to handle large volumes of data efficiently. - Must allow for schema-less data storage to accommodate unstructured and semi-structured data. - Should support distributed computing and high availability to minimize downtime. - Not just for read-heavy applications; must also effectively manage write-heavy workloads.
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