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Top 26 Vector Database Software SaaS Companies in May 2026

As of May 2026, there are 26 SaaS companies in Vector Database Software. They have combined revenues of $20.6B and employ 13.4K people. They have raised $18.5B and serve 2M customers combined.

Vector Database Software is designed to store, manage, and retrieve high-dimensional data representations, typically in the form of vectors. These databases enable efficient similarity searches and rapid data retrieval, which are essential for applications like machine learning and artificial intelligence. Primary use cases include natural language processing, recommendation systems, and image or video search, where traditional databases fall short in handling complex data structures.

Companies
26
Revenue
$20.6B
Funding
$18.5B
Employees
13.4K

Filters

Sorting: Highest -> Lowest

Filters
Revenue
All<$1M$1M-$5M$5M-$10M$10M-$100M$100M+
Funding (Locked)Growth (Locked)Team-Size (Locked)

Top Vector Database Software Companies

Showing 10 of 3 companies ranked by annual revenue.

1
ApertureData

Mountain View, California, United States

ApertureDB simplifies the complexities of handling images, videos, and related metadata. We use a graph database to combine keyword and label search with vector search and multimodal data management to give you a single data layer for all your multimodal AI needs. ApertureDB is not just an enterprise ready vector database for unstructured data, but goes beyond that to provide a unified data layer to seamlessly support your entire machine learning pipeline. Try ApertureDB: https://www.aperturedata.io/demo-request

Revenue
$990K
Customers
-
Year founded
2018
Funding
-
Team size
9
Growth
-
2
Pulse

San Francisco, California, United States

Pulse's mission is to improve workplace culture by creating transparency and open communication through an anonymous community.

Revenue
$591.7K
Customers
-
Year founded
2009
Funding
-
Team size
1
Growth
89.48%
3
Graphium Labs

Vancouver, British Columbia, Canada

HyperGraph is both a database and compute platform designed from the ground up to maintain one key property: its ability to scale. No matter how large of a change in data or compute scale you require, HyperGraph is designed to handle it.

Revenue
$330K
Customers
-
Year founded
2024
Funding
-
Team size
3
Growth
-

Inclusion Criteria

- Must efficiently store and index high-dimensional vectors. - Should support fast retrieval and similarity search capabilities. - Must provide capabilities for CRUD (Create, Read, Update, Delete) operations specifically for vector data. - Should allow for metadata filtering to enhance search results. - Not just a general-purpose database; must be optimized specifically for vector data handling.