MongoDB Atlas Vector Search
51/100Vector search built into Atlas document DB; managed clusters.
mongodb.com// scorecard · 51/100
verified 1mo agoAgent-readiness23/35
Agent registration (api_key)6/9
Public API5/5
OpenAPI spec0/9
MCP server9/9
llms.txt3/3
Reliability & performance0/15
Actively maintained—
Production-ready0/4
Updated recently—
Pricing12/13
Itemized public pricing6/6
Free tier / trial4/4
Free-tier generosity2/3
Docs & DX2/12
Docs quality—
Public API2/2
Quickstart / examples0/2
Security & compliance10/12
SOC 26/6
ISO 270012/2
GDPR0/2
Security / trust page2/2
Openness4/10
Open source0/6
Open / un-gated API4/4
Company maturity0/3
Company size—
Years operating—
// rankings · cost per standard workload
#13 in Vector Databasesnot comparable
Cluster/instance-based; HNSW needs ~M20 (~$146) or a Search Node — sizing-dependent
mongodb.com/pricing// overview
MongoDB Atlas Vector Search integrates operational and vector databases in a single unified platform on AWS, Azure, and Google Cloud. It uses vector representations of data to perform semantic search, build recommendation engines, design Q&A systems, detect anomalies, or provide context for generative AI apps. It combines operational data, vectors, and streaming data for intelligent applications.
// pricing
Free tier · generosity 3/5
Includes: M0 cluster: 512MB storage · Shared RAM/vCPU · Atlas Vector Search included at no extra cost · Free forever, no card required
Limits: Up to 100 ops/sec · 32MB sort memory · No backups · Vector/search index management on M0 must be done via Atlas UI, not programmatically
Free$0/hour
- 512MB of storage
- Shared RAM
- Shared vCPU
Flex$0.011/hour
- 5GB of storage
- Shared RAM
- Shared vCPU
Dedicated$0.08/hour
- 10GB to 4TB of storage
- 2GB to 768GB RAM
- 2vCPUs to 96vCPUs
// security & compliance
✓ SOC 2✓ ISO 27001✗ GDPR✗ HIPAA
// features
- semantic search
- recommendation engines
- Q&A systems
- anomaly detection
- generative AI context
- unified operational and vector data platform