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Top 13 NoSQL Databases SaaS Companies in May 2026

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.

Companies
13
Revenue
$952M
Funding
$1.9B
Employees
4.1K

Filters

Sorting: Highest -> Lowest

Filters

Top NoSQL Databases Companies

Showing 10 of 4 companies ranked by annual revenue.

1
SurrealDB

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.

Revenue
$5M
Customers
-
Year founded
2022
Funding
-
Team size
45
Growth
-
2
PlanetScale

San Francisco, California, United States

Developer of a database management platform designed to improve performance and scale massively. The company's platform combines many important MySQL features with the scalability of a NoSQL database, as well as offers various features to improve performance, handle failovers, backups and manage shards, among others, enabling businesses to segment their database to boost memory efficiency without sacrificing reliable access speeds.

Revenue
$3.9M
Customers
-
Year founded
2018
Funding
$105M
Team size
93
Growth
106.16%
3
Alachisoft

Dallas, Texas, United States

Use NCache to remove Data related performance bottlenecks!

Revenue
$3.8M
Customers
-
Year founded
1996
Funding
-
Team size
76
Growth
73.22%
4
Quasardb

Paris, Ile-de-france, France

Developer of a software storage technology designed to feed processors doing risk computations and receive the results reliably. The company's software storage technology develops a database management system based on not only structured query language (NoSQL) for hyperscalable architecture, enabling clients to avail high-performance, distributed and column-oriented database with native time series support.

Revenue
$1.6M
Customers
-
Year founded
2008
Funding
-
Team size
8
Growth
37.43%

Inclusion Criteria

- 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.