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Top 13 Key Value Databases SaaS Companies in May 2026

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.

Companies
13
Revenue
$1.1B
Funding
$811.2M
Employees
7.4K

Filters

Sorting: Highest -> Lowest

Filters

Top Key Value Databases Companies

Showing 10 of 1 companies ranked by annual revenue.

1
BangDB

Bangalore, Karnataka, India

BangDB is a multimodal converged database platform. BangDB simplifies and speeds up the development of modern use cases, features by avoiding the middle layer developments by the users. BangDB handles the application logic using schema defined and customized by the user, this not only decreases the cost of development but also ships newer features faster and with higher quality. BangDB natively converges following. 1. Document database, with primary, secondary, composite, geospatial, reverse indexing 2. Stream processing for real-time time-series events, patterns, anomalies, running stats 3. Graph processing at scale, cypher like query language with implicit AI 4. Integrated AI, ML ops, Resource servers for larger files like models etc. 4. Vector indexing for RAG workflows * 5. Workflow engine with groups and pipes for enabling complex processing logic and flow 6. High performance database for devices, clouds or p2p based computing BangDB has proved to be valuable for Fintech, Retails, Ecommerce, Healthcare, CRM, Infra, Devops, IOT for several use cases. Real-time monitoring and actions, similarities, personalization & recommendations, fraud and threat detection, CRM (customer experience), visitor insights for real-time interactions, Infra/app/log monitoring, master data management etc. are some of the use cases where BangDB scales with cost savings, accelerated app development and delivery with higher quality.

Revenue
$660K
Customers
-
Year founded
2015
Funding
-
Team size
6
Growth
-

Inclusion Criteria

- 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.