As of May 2026, there are 42 SaaS companies in Database Software. They have combined revenues of $1.2B and employ 6.9K people. They have raised $2.6B and serve 10K customers combined.
Database Software refers to applications designed to create, manage, and analyze structured data. These tools facilitate various use cases such as data storage, retrieval, and manipulation, enabling organizations to efficiently manage their data resources. Users typically include IT professionals, data analysts, software developers, and business managers who rely on accurate data to inform their decisions and operations.
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Showing 10 of 42 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.
Wilmington, Delaware, United States
EDB Postgres® AI (EDB PG AI) is the first open, enterprise-grade sovereign data and AI platform—secure, compliant, and scalable, on-premises and across clouds. Built on Postgres, the world’s leading database, EDB PG AI unifies transactional, analytical, and AI workloads, enabling organizations to operationalize their data and LLMs while maintaining control over sovereign environments. EDB PG AI is supported by a global partner network and delivers up to 99.999% availability as well as hybrid management and a built-in AI factory. As one of the most active contributors to the PostgreSQL project, EDB is deeply invested in the vitality of the global community. To learn more, visit www.enterprisedb.com.
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
Chantilly, Virginia, United States
US Information Technologies provide oracle based information technology solutions and services.
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.
Redwood City, California, United States
ClickHouse is an open-source, column-oriented OLAP database management system that allows users to generate analytical reports using SQL queries in real-time. Its technology works 100-1000x faster than traditional database management systems, and processes hundreds of millions to over a billion rows and tens of gigabytes of data per server per second. With a widespread user base around the globe, the technology has received praise for its reliability, ease of use, and fault tolerance. Learn more at clickhouse.com.
- Must allow users to store, retrieve, and manipulate structured data - Should provide data management capabilities such as backup, recovery, and security - Must support various data models, including relational, NoSQL, and multi-model - Should include features for data analysis and reporting - Not just a data storage solution; must also offer data querying and management tools - Must cater to technical users, such as DBAs and data scientists, as well as non-technical business users
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