10 Best Vector Databases of 2026

1. 1

   Pinecone

   A fully managed vector database with dense, sparse and full-text indexes, hosted inference and a RAG assistant.

   8.8overall

   A fully managed vector database with dense, sparse and full-text indexes, hosted inference and a RAG assistant.

   Best forTeams that want a dedicated managed vector store with published per-unit prices and no servers to size.

   Adoption data

   10,000Pinecone says its database, Nexus and Marketplace products serve more than 10,000 customers and 1 million developers worldwide.

   Pinecone, Company (2026): “power accurate, fast, and cost-effective AI applications for more than 10,000 customers and 1M developers worldwide.”

   Pinecone is a managed vector database that hides capacity planning behind usage-based pricing. Its company page says the platform serves more than 10,000 customers and 1 million developers, the largest customer count published by a dedicated vector store in this list. Every plan supports dense, sparse and full-text indexes and hosted embedding and reranking models, and Pinecone Assistant adds a ready RAG layer. The Starter plan is free with up to 2 GB of storage, Builder costs $20 per month flat for small teams, and Standard sets a $50 monthly minimum, then bills $0.33 per GB per month for storage, $4 to $4.50 per million write units and $16 to $18 per million read units depending on region. Scale limits are generous at the top: Enterprise allows 1,000,000 namespaces per index and adds bring your own cloud and a 99.95% uptime SLA. The trade-off is lock-in, since the engine is not open source. We compared documented features and published prices.

   Strengths

   • +Clear per-unit prices: $0.33 per GB per month for storage on Standard
   • +Builder plan at $20 per month flat is easy to budget for small teams
   • +Standard trial includes $300 of credits over 3 weeks

   Limitations

   • −Closed source, so there is no self-hosted option outside BYOC
   • −Standard has a $50 monthly minimum and Enterprise a $500 minimum
   • −HIPAA compliance costs $190 per month as an add-on

   SummaryMore than 10,000 customers, the largest customer count published by a dedicated vector database here.

2. 2

   MongoDB Atlas Vector Search

   Vector and hybrid search built into the MongoDB Atlas document database, with automated embeddings from Voyage AI.

   8.7overall

   Vector and hybrid search built into the MongoDB Atlas document database, with automated embeddings from Voyage AI.

   Best forTeams whose application data already lives in MongoDB and who want vectors in the same database.

   Adoption data

   29%MongoDB reported that Atlas revenue grew about 29% year over year in its fiscal 2027 second quarter, which ended July 31, 2026.

   MongoDB, MongoDB, Inc. Announces Second Quarter Fiscal 2027 Financial Results (Form 8-K, Exhibit 99.1) (2026): “Atlas revenue up approximately 29% year-over-year in the second quarter fiscal 2027”

   MongoDB Atlas Vector Search puts embeddings next to the documents they describe, so a retrieval app can filter on metadata, run lexical search and rank by vector similarity in one query. MongoDB's fiscal 2027 second quarter filing put Atlas revenue growth at about 29 percent, and 19.0 percent of database respondents in the 2026 Stack Overflow Developer Survey used MongoDB, which gives this option the broadest installed base in the list. Automated Embedding generates and syncs vectors with Voyage AI models hosted inside Atlas, and the service supports scalar and binary quantization. Dedicated Search Nodes isolate vector workloads from the main cluster when traffic grows. Atlas has a free tier, and Flex clusters cost $0.011 per hour with a $30 monthly cap. The limits are worth checking: embeddings must stay under 4,096 dimensions, and Search Nodes are billed on top of the cluster. Teams not already on MongoDB may prefer a dedicated store. We compared documented features and published prices.

   Strengths

   • +No separate vector store or sync pipeline for MongoDB users
   • +The only vendor here that reports growth for the underlying platform in SEC filings
   • +Flex tier has a hard $30 monthly cap for prototypes

   Limitations

   • −Embeddings are limited to 4,096 dimensions
   • −Document model, so it fits less well for teams standardized on SQL
   • −Search Nodes for heavy vector workloads add a separate hourly cost

   SummaryAtlas revenue grew about 29% year over year, the only SEC-filed growth figure behind a vector option here.

3. 3

   Qdrant

   An open-source vector search engine written in Rust, offered as a managed cloud, hybrid cloud or self-hosted.

   8.5overall

   An open-source vector search engine written in Rust, offered as a managed cloud, hybrid cloud or self-hosted.

   Best forDevelopers who want an open-source engine with strong filtering and quantization, plus a managed option.

   Adoption data

   250 millionQdrant reports more than 250 million downloads of its open-source engine and about 29,000 GitHub stars.

   Qdrant, About Us (2026): “250+ Million Downloads 29K GitHub Stars”

   Qdrant is an open-source vector search engine written in Rust, and its about page reports more than 250 million downloads and about 29,000 GitHub stars, the largest download figure among the open-source engines here. Its strength is filtered search: filters run during HNSW graph traversal rather than before or after it, and metadata conditions cover nested fields, text, geo and vector presence. Hybrid search blends dense and sparse vectors, and version 1.20 adds BM25 without sparse vectors. Scalar, binary and asymmetric quantization cut memory by up to 64 times. Qdrant Cloud has a free forever single-node cluster with 1 GB of RAM and 4 GB of disk, and the Standard tier bills by cluster resources with a 99.9 percent SLA, rising to 99.95 percent across zones. The pricing page does not print a USD rate card, so we list the paid price as pending. SSO and private links need Premium. We compared documented features and published prices.

   Strengths

   • +Free forever cluster with 1 GB RAM and 4 GB disk
   • +Same engine runs locally, in your cloud or in Qdrant Cloud
   • +Standard tier SLA of 99.9% on single AZ and 99.95% on multi AZ

   Limitations

   • −Paid cloud prices sit behind a calculator, not a published rate card on the pricing page
   • −SSO and private VPC links require the Premium tier with a minimum spend
   • −Serverless is still on a waitlist

   SummaryMore than 250 million downloads, the highest reach among the open-source vector engines in this list.

4. 4

   Supabase Vector

   Hosted Postgres with the pgvector extension, plus auth, storage and edge functions in one project.

   8.4overall

   Hosted Postgres with the pgvector extension, plus auth, storage and edge functions in one project.

   Best forDevelopers who want vectors in Postgres with SQL joins and a full backend, without a separate vector service.

   Adoption data

   10 millionSupabase said in its 2026 Series F announcement that nearly 10 million developers build on its platform.

   Supabase, Supabase Series F (2026): “Nearly 10 million developers build on Supabase today, more than doubling since our last fundraising announcement eight months ago.”

   Supabase Vector is the pgvector route to retrieval: embeddings live in a Postgres table, so you can join them with users, permissions and product data in plain SQL. Supabase's Series F post says nearly 10 million developers build on the platform, the largest developer base of any platform in this list. The vector module adds client libraries for managing vector stores and examples for semantic search and chatbot memory, and the same project includes auth, storage, edge functions and realtime. The Free plan includes a 500 MB database, and Pro costs $25 per month with 8 GB of disk per project, then $0.125 per GB. The trade-off is that pgvector runs inside a general database, so tens of millions of vectors call for careful index choices and larger compute. Dedicated vector stores offer more tuning for that scale. We compared documented features and published prices.

   Strengths

   • +Vectors join directly with relational data in SQL
   • +Flat $25 Pro plan with 8 GB of disk per project
   • +Largest developer base of any platform in this list

   Limitations

   • −Built on a general Postgres instance, so very large vector sets need careful index and memory sizing
   • −Free plan database is capped at 500 MB
   • −No hosted embedding models or reranking in the vector module itself

   SummaryNearly 10 million developers, and vectors that join with relational data in standard SQL.

5. 5

   turbopuffer

   A serverless vector and full-text search engine built on object storage with a memory and SSD cache.

   8.4overall

   A serverless vector and full-text search engine built on object storage with a memory and SSD cache.

   Best forTeams with huge multi-tenant corpora who want low storage cost and very high namespace counts.

   Adoption data

   1 trillionturbopuffer reports that its production systems handle more than 1 trillion documents, 10 million writes per second and 100,000 queries per second.

   turbopuffer, turbopuffer: fast search engine built on object storage (2026): “1T+ documents, 10M+ writes/s , and 100k+ queries/s in prod”

   turbopuffer stores vectors and text indexes on object storage and serves queries from a memory and SSD cache, which keeps the price of cold data low. Its homepage reports more than 1 trillion documents, 10 million writes per second and 100,000 queries per second in production, and lists customers such as Notion, Linear, Atlassian and Anthropic. The documented limits suit multi-tenant apps: unlimited namespaces, up to 128B documents per namespace and 5k+ queries per second per namespace. Search covers vectors, full text and hybrid queries with metadata filters. The Launch plan has a $16 monthly minimum and includes all database features and a SOC 2 report; Scale starts at a $256 minimum and adds SSO, audit logs and a HIPAA-ready BAA. Usage is billed per GB stored, written and queried. There is no free plan, and adoption is stated as volume rather than a customer count, so we score it below the leaders. We compared documented features and published prices.

   Strengths

   • +Lowest paid minimum among the dedicated vector stores here at $16 per month
   • +Storage priced at up to $0.33 per GB, with writes at up to $2.00 per GB
   • +Very high documented limits for multi-tenant apps

   Limitations

   • −No free plan
   • −Adoption is reported as production volume, not a customer count
   • −Enterprise has a $4,096 monthly minimum and a 35% usage premium

   SummaryMore than 1 trillion documents in production and no published cap on namespaces.

6. 6

   Zilliz Cloud

   The managed service for the open-source Milvus vector database, with serverless, dedicated and BYOC deployments.

   8.4overall

   The managed service for the open-source Milvus vector database, with serverless, dedicated and BYOC deployments.

   Best forTeams with very large vector collections that want managed Milvus and a choice of cost or speed profiles.

   Adoption data

   10,000Zilliz, the company behind Milvus, says more than 10,000 enterprise users rely on its vector database technology.

   Zilliz, About Zilliz (2026): “$113 M Investment 10,000+ Enterprise users”

   Zilliz Cloud is the managed service from the company that created Milvus, one of the most widely used open-source vector databases. Zilliz says more than 10,000 enterprise users rely on its technology, and its site describes production use with 100B+ entities and 10K+ QPS. The pricing page makes scale limits concrete. A performance-optimized compute unit holds 2 million vectors with 500 to 1,500 QPS and about 10 ms latency, while a capacity-optimized unit holds 8 million vectors from $16 per million vectors per month. The Free tier includes 5 GB of storage and up to 5 collections, Standard serverless is pay as you go from $0 per month, dedicated clusters start at $126 per month, and Enterprise starts at $197 per month with SSO, audit logs and a 99.95 percent SLA. Search covers vectors, text, JSON and geospatial data. Teams new to Milvus should budget time to size compute units. We compared documented features and published prices.

   Strengths

   • +Free tier with 5 GB of storage and up to 5 collections
   • +Cluster types let you trade latency for cost on large datasets
   • +30-day free trial on Standard and Enterprise plans

   Limitations

   • −Dedicated clusters start at $126 per month, higher than several rivals
   • −SSO, audit logs and a 99.95% SLA need the Enterprise plan from $197 per month
   • −Compute unit sizing takes planning for teams new to Milvus

   SummaryPublished per-CU capacity and latency figures make scale planning easier than on most rivals.

7. 7

   Redis Cloud

   Managed Redis with the Redis Query Engine for vector, hybrid and exact-match search in memory.

   8.3overall

   Managed Redis with the Redis Query Engine for vector, hybrid and exact-match search in memory.

   Best forTeams already using Redis for caching who want low-latency vector search and semantic caching in the same store.

   Adoption data

   28.3%In the 2026 Stack Overflow Developer Survey, 3,414 respondents, or 28.3% of those who answered the database question, said they used Redis.

   Stack Overflow, 2026 Developer Survey: Databases (2026): “Redis 3,414 28.3%”

   Redis Cloud adds vector search to the in-memory store many teams already run for caching and sessions. In the 2026 Stack Overflow Developer Survey, 28.3 percent of database respondents used Redis, the highest usage share of any product in this list. The Redis Query Engine handles vector search alongside exact-match and structured queries, so an app can filter on fields and rank by similarity in one call, and Redis promotes the same store for semantic caching of LLM answers. Pricing starts low. The Free plan offers a 30 MB database, Essentials starts at $0.007 per hour, about $5 per month, for shared deployments from 250 MB to 100 GB, and Pro starts at $0.014 per hour with a $200 monthly minimum, adding active-active regions and up to 99.999 percent uptime. Redis Flex moves part of the data to SSD. The catch is memory cost: large embedding sets get expensive in RAM. We compared documented features and published prices.

   Strengths

   • +Cheapest fixed paid entry in this list at about $5 per month
   • +Used by 28.3% of database respondents in the 2026 Stack Overflow survey
   • +Vectors sit next to cache, session and feature data

   Limitations

   • −Free plan is only 30 MB, too small for most embedding sets
   • −Essentials is a shared deployment capped at 100 GB
   • −Pro requires a $200 monthly minimum

   SummaryThe most used database in this list per the 2026 Stack Overflow survey, with paid plans from about $5 per month.

8. 8

   Weaviate

   An open-source AI database with hybrid search, built-in embeddings and a natural-language Query Agent.

   8.3overall

   An open-source AI database with hybrid search, built-in embeddings and a natural-language Query Agent.

   Best forTeams that want an open-source vector database with hosted embedding and agent services on the same bill.

   Adoption data

   15 millionWeaviate reports more than 15 million downloads of its open-source database and more than 16,300 GitHub stars.

   Weaviate, About us (2026): “15,000,000+ Downloads 16,300+ GitHub stars”

   Weaviate is an open-source AI database that pairs vector storage with hosted services. Its about page reports more than 15 million downloads and more than 16,300 GitHub stars. Every plan includes hybrid search, vector compression and multi-tenancy, and you can choose a cost-optimized HFresh index or an in-memory HNSW profile. Weaviate Embeddings provides hosted models from $0.025 per million tokens, and the Query Agent converts plain-language questions into database operations, with 1,000 free requests a month. The Free forever cluster holds 100,000 objects with 1 GB of memory and 10 GB of disk. Flex starts at $45 per month pay as you go, with vector dimensions from $0.00465 per million and storage from $0.12 per GiB, and supports up to 1,000 collections. Flex runs on shared infrastructure with a 99.5 percent SLA, so production teams needing SSO or 99.95 percent uptime must sign a Premium contract. We compared documented features and published prices.

   Strengths

   • +Free forever cluster with 100,000 objects, 1 GB memory and 10 GB disk
   • +Open source, so the same database can be self-hosted
   • +Embeddings and agent features ship with the cloud service

   Limitations

   • −Flex is a shared cluster with a 99.5% uptime SLA
   • −SSO, phone support and higher SLAs need a Premium contract
   • −Vector dimension pricing varies by index type, compression and region

   SummaryHosted embeddings and a Query Agent bundled with an open-source vector database.

9. 9

   Elastic Cloud (Elasticsearch)

   Elasticsearch as a vector database, with serverless and hosted deployments, Jina AI models and agent tooling.

   8.0overall

   Elasticsearch as a vector database, with serverless and hosted deployments, Jina AI models and agent tooling.

   Best forTeams that already run Elasticsearch for search or logs and want vectors and keyword relevance together.

   Adoption data

   14.8%In the 2026 Stack Overflow Developer Survey, 1,784 respondents, or 14.8% of those who answered the database question, said they used Elasticsearch.

   Stack Overflow, 2026 Developer Survey: Databases (2026): “Elasticsearch 1,784 14.8%”

   Elasticsearch has grown from a keyword search engine into a vector database, and Elastic now sells it for retrieval and context engineering. In the 2026 Stack Overflow Developer Survey, 14.8 percent of database respondents used Elasticsearch, so many teams already have a cluster and the skills to run it. The main benefit is combining mature BM25 keyword relevance with vector similarity in one engine, which helps with product names, codes and other exact terms that embeddings miss. Elastic Inference Service offers Jina AI embedding and reranker models, and Agent Builder adds tooling for agents. Elastic Cloud Serverless bills search from $0.09 per VCU per hour and ingest from $0.14, and vector profiles get 50 GB of storage free; Elastic's own example puts a small dev environment at about $24 per month. There is no permanent free cloud plan, and VCU billing takes some modelling before you can forecast a bill. We compared documented features and published prices.

   Strengths

   • +Mature keyword search and relevance tuning next to vectors
   • +Vector profiles receive 50 GB of storage free on serverless
   • +Self-managed option for teams that cannot use a cloud service

   Limitations

   • −VCU-based billing is harder to estimate than flat plans
   • −No permanent free cloud plan
   • −Heavier to operate than a dedicated vector store for vector-only apps

   SummaryThe deepest keyword relevance tooling in this list, combined with vector search in one engine.

10. 10

    Chroma Cloud

    Open-source search infrastructure for AI, offered as a serverless cloud on object storage.

    7.9overall

    Open-source search infrastructure for AI, offered as a serverless cloud on object storage.

    Best forDevelopers who prototype with open-source Chroma and want a serverless cloud with usage pricing.

    Adoption data

    15 millionChroma reports more than 15 million monthly downloads of its open-source package and about 27,000 GitHub stars.

    Chroma, Chroma: open-source search infrastructure for AI (2026): “15M+ monthly downloads Apache 2.0 27k Github stars”

    Chroma began as the open-source embedding store many developers reach for in their first RAG prototype, and its homepage reports more than 15 million monthly downloads and about 27,000 GitHub stars. Chroma Cloud runs the same API as a serverless service on object storage with automatic tiering. Search covers dense vectors, sparse BM25 and SPLADE vectors, full text, regex and metadata, and forking lets teams version datasets or test changes. Documented limits are 1M collections per database and 5M records per collection, which suits many small indexes better than one huge one. Pricing is usage-based: $2.50 per GiB written, $0.33 per GiB stored per month and $0.0075 per TiB queried. Starter is $0 plus usage with $5 in credits, and Team costs $250 per month plus usage with $100 in credits and SOC 2. Chroma has also announced it is joining Replit, so buyers should watch roadmap updates. We compared documented features and published prices.

    Strengths

    • +Starter plan is $0 plus usage with $5 in free credits
    • +Clear usage rates: $2.50 per GiB written and $0.33 per GiB stored
    • +Same API from a local install to the cloud

    Limitations

    • −Team plan jumps to $250 per month plus usage
    • −5M records per collection is lower than several rivals
    • −Service pauses when a usage limit is reached until the limit changes

    SummaryMore than 15 million monthly downloads and one API from laptop to serverless cloud.

Questions or corrections: editorial@statlyst.com · Disclosure