Vector Databases Landscape 2026
The 15 published vector databases filed under vector databases, positioned on the same axes as the whole category: public evidence and recent publication activity, measured against every vector databases product rather than only against each other.
Scroll the chart sideways to read every position, or browse the complete list below. Each tool links to its review, pricing, alternatives, and comparisons.
Where Each Tool Lands
Strong & Rising (3)
- MilvusFree (open source)
Vector Database
Public signal strength: 90th percentile · Recent release activity: 100th percentile
GitHub stars:46.2k - WeaviateFree tier
Vector Database
Public signal strength: 70th percentile · Recent release activity: 50th percentile
GitHub stars:16.8k - FAISSFree (open source)
Vector Database
Public signal strength: 60th percentile · Recent release activity: 70th percentile
GitHub stars:40.9k
Strong & Steady (2)
Building Activity (2)
Lower Visibility (2)
- ChromaDBUsage-based
Vector Database
Public signal strength: 40th percentile · Recent release activity: 10th percentile
GitHub stars:29.3k - MongoDB Atlas Vector SearchContact sales
Vector Database
Public signal strength: 0th percentile · Recent release activity: 20th percentile
Not yet plotted (6)
Listed alphabetically. A product appears here when its public evidence does not meet the positioning threshold, when it has no recent verified first-party publication activity, or when it falls outside the category chart limit. Missing evidence is shown as missing, never converted to zero. A tool we could not measure is listed without a position rather than placed at the bottom of the scale.
How to read this view
A tool must show measured activity on at least 2 different platforms, at least one of which must be a primary source (Google Trends, GitHub, Docker Hub, npm, PyPI, Hugging Face and Stack Overflow); Hacker News and Product Hunt can supply the second. The horizontal position shows that evidence: Measured activity on each qualifying platform (Google Trends, GitHub, Docker Hub, npm, PyPI, Hugging Face, Stack Overflow, Hacker News and Product Hunt), log-normalized and percentile-ranked within the category. Each platform counts once and is capped, so breadth of evidence counts for more than a single large number. The vertical position shows Recent verified first-party publication activity — a GitHub release, or an npm, PyPI, Docker Hub or Hugging Face publish. A product with no public repository or package cannot have this signal, so tools without one are listed rather than positioned. Both percentiles are computed across the whole vector databases category, so a product keeps the same position here as on the category chart. This measures how much verifiable public evidence exists for a tool. It is not a measure of product quality, market share, customer count, or enterprise adoption. Missing evidence is shown as missing, never converted to zero. A tool we could not measure is listed without a position rather than placed at the bottom of the scale.