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List of the Best Vector Database Software in 2026

Rajat Gupta
Researched and Edited by Rajat Gupta
Rajat Gupta

Researched and Edited by Rajat Gupta

Last updated: · How we review

Editor's Summary · Vector Database Software

Start with where your data already lives, because that decides more than benchmark numbers do. If you run Postgres, pgvector keeps embeddings beside the rows they describe and removes an entire system from the stack — for most applications that is the right answer and the cheapest one. If you run MongoDB, Atlas Vector Search does the same thing. Elasticsearch, Redis, ClickHouse and SingleStore all now do vectors too.

Reach for a dedicated engine when scale or recall genuinely demands it. Pinecone is the managed default, Milvus and Qdrant are the open-source options at serious scale, and Weaviate and Chroma sit closer to the developer-experience end.

The cost model deserves more attention than it usually gets. Keeping a large index in memory is expensive, which is why turbopuffer and Upstash Vector serve from object storage and bill per request — a much better fit for multi-tenant products where most indexes are idle.

And check filtering carefully. Nearly every engine claims metadata filtering; the difference is whether it filters before or after the nearest-neighbour search, which changes both recall and latency.

Quick picks for Vector Database Software

  • Best if you already run Postgrespgvector
  • Best managed dedicated enginePinecone
  • Best open-source at scaleMilvus

Who gets the most from Vector Database Software

  • 1Engineers building retrieval-augmented generation over a document corpus
  • 2Platform teams choosing between extending Postgres and running a dedicated engine
  • 3Teams running multi-tenant search where most indexes are idle most of the time
How to choose Vector Database Software

Check whether your current database already supports vectors before adding a system to operate — for most applications pgvector or Atlas Vector Search is sufficient and removes a synchronization problem. If you do need a dedicated engine, test with your real corpus and your real filters, since pre-filter versus post-filter behavior changes results in ways a generic benchmark will not show. Weigh the cost model against your access pattern: an index that is queried rarely does not justify provisioned memory.

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Showing 1-20 out of 24

9.8

SpotScore

Elasticsearch - Site Search Software

Elasticsearch

Empower your website with intelligent search capabilities.

Best for: SMB teams · Mid-market · Enterprise

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What is Elasticsearch?

Elasticsearch brings the power of full-text search to the website, turning it into an information hub that enables intelligent navigation of content. This takes site to another level, providing additional functionality as well as improving usability and conversion rates. Elasticsearch is a ...

Read more about Elasticsearch

Elasticsearch offers custom pricing plan

9.0

SpotScore

Weaviate logo

Weaviate

Open-source vector database for semantic search, RAG, and AI-native applications

Best for: SMB teams

Try for Free

4.5

Add to compare

watch-demo

Watch Demo

What is Weaviate?

Weaviate is an open-source vector database designed for AI-native applications. It stores, indexes, and searches high-dimensional vector embeddings alongside structured data, enabling semantic search, RAG (retrieval-augmented generation), and recommendation systems. Weaviate natively integrates ...

Read more about Weaviate

Starts from Freefree, also offers free forever plan

Spotsaas Buyer Intelligence

See the companies researching Vector Database software right now — while they're still comparing options.

In-market Vector Database buyersCompany-level namesNo pixel to install

7.6

SpotScore

SingleStore - Database Management Software

SingleStore

Efficiently organize and grow your business.

Best for: SMB teams · Mid-market · Enterprise

Start Free Trial

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What is SingleStore?

SingleStore is comprehensive data management software that makes it easy to organize and grow business. This software helps user to manage store locations, sales figures, customer information and inventory efficiently and effectively. SingleStore allows user to easily maintain a single, ...

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SingleStore offers custom pricing plan

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Typesense - Logo

Typesense

Open-source search engine with vector and hybrid search

Best for: SMB teams · Mid-market · Enterprise

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What is Typesense?

Typesense is an open-source search engine positioned as a simpler alternative to Elasticsearch, with typo tolerance and fast faceted search out of the box, and support for vector and hybrid search alongside keyword matching. It is designed to be operable without a dedicated search team — ...

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Typesense offers custom pricing plan

Deep Lake - Logo

Deep Lake

Database for AI storing vectors alongside raw multimodal data

Best for: SMB teams · Mid-market · Enterprise

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What is Deep Lake?

Deep Lake from Activeloop stores vectors together with the underlying data — images, video, audio, text — in a format designed for machine learning workflows, supporting version control over datasets and streaming to training jobs. Its distinguishing idea is treating the vector index and the ...

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Deep Lake offers custom pricing plan

pgvector - Logo

pgvector

Vector similarity search as a PostgreSQL extension

Best for: SMB teams · Mid-market · Enterprise

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What is pgvector?

pgvector adds vector storage and similarity search to PostgreSQL as an extension, so embeddings live in the same database as the relational data they relate to. That removes the operational burden of running a second datastore and lets a single SQL query filter on business columns and rank by ...

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pgvector offers custom pricing plan

What buyers evaluate in Vector Database Software
Whether your existing database can do this, before adding a dedicated engine
Whether metadata filtering happens before or after the vector search, which changes recall and latency
Cost model: provisioned memory versus object storage and per-request billing
Meilisearch - Logo

Meilisearch

Developer-friendly search with hybrid keyword and vector retrieval

Best for: SMB teams · Mid-market · Enterprise

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What is Meilisearch?

Meilisearch is an open-source search engine focused on developer experience and instant results, with typo tolerance, faceting and, more recently, hybrid search that blends keyword relevance with vector similarity. It is designed to be integrated quickly and tuned through simple ranking rules ...

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Meilisearch offers custom pricing plan

Vespa - Logo

Vespa

Search and recommendation engine with native vector and tensor support

Best for: SMB teams · Mid-market · Enterprise

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What is Vespa?

Vespa is a search and recommendation platform that handles vector search, text search and structured filtering in one query, with a tensor model that supports ranking logic well beyond nearest-neighbour lookup. Originally built at Yahoo, it is designed for serving large corpora with low latency ...

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Vespa offers custom pricing plan

ClickHouse - Logo

ClickHouse

Columnar OLAP database with vector similarity functions

Best for: SMB teams · Mid-market · Enterprise

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What is ClickHouse?

ClickHouse is a columnar analytical database that also supports vector similarity search through distance functions and approximate nearest-neighbour indexes, letting teams run vector retrieval alongside large-scale analytical queries in one system. It is not a purpose-built vector database, ...

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ClickHouse offers custom pricing plan

Upstash Vector - Logo

Upstash Vector

Serverless vector database priced per request

Best for: SMB teams · Mid-market · Enterprise

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What is Upstash Vector?

Upstash Vector is a serverless vector database billed per request rather than per provisioned instance, with no cluster to size or keep running. It supports metadata filtering, namespaces and hybrid search, and includes built-in embedding models so vectors can be generated at write time. The ...

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Upstash Vector offers custom pricing plan

LanceDB - Logo

LanceDB

Embedded multimodal vector database on the Lance columnar format

Best for: SMB teams · Mid-market · Enterprise

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What is LanceDB?

LanceDB is a vector database built on the Lance columnar format, designed to run embedded in an application or over object storage rather than as a separate cluster. It stores vectors alongside the source data — text, images, video — so retrieval returns the record rather than an ID to look up ...

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LanceDB offers custom pricing plan

Redis - Logo

Redis

In-memory data store with vector similarity search

Best for: SMB teams · Mid-market · Enterprise

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What is Redis?

Redis supports vector similarity search alongside its established role as an in-memory data store, cache and message broker, using HNSW and flat indexes with hybrid filtering on metadata. Because the vectors sit in memory, query latency is very low, and teams already running Redis avoid ...

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Redis offers custom pricing plan

Vertex AI Vector Search - Logo

Vertex AI Vector Search

Google Cloud managed vector search at very large scale

Best for: SMB teams · Mid-market · Enterprise

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What is Vertex AI Vector Search?

Vertex AI Vector Search is Google Cloud's managed nearest-neighbour service, derived from the ScaNN algorithm developed by Google Research and built for indexes running into billions of vectors with low query latency. It handles index building, sharding and serving, and integrates with Vertex ...

Read more about Vertex AI Vector Search

Vertex AI Vector Search offers custom pricing plan

Marqo - Logo

Marqo

Vector search with embedding generation built in

Best for: SMB teams · Mid-market · Enterprise

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What is Marqo?

Marqo handles embedding generation and vector search in one system, so documents and queries are vectorised by the engine rather than by a separate pipeline the team maintains. It supports text and image search with multimodal models, and is positioned strongly around ecommerce product ...

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Marqo offers custom pricing plan

MongoDB Atlas Vector Search - Logo

MongoDB Atlas Vector Search

Vector search inside the MongoDB Atlas document database

Best for: SMB teams · Mid-market · Enterprise

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What is MongoDB Atlas Vector Search?

Atlas Vector Search adds approximate nearest-neighbour search to MongoDB Atlas, so embeddings are stored as fields on the documents they describe and queried through the standard aggregation pipeline. Vector similarity, document filters and joins compose in one query, and there is no second ...

Read more about MongoDB Atlas Vector Search

MongoDB Atlas Vector Search offers custom pricing plan

Milvus - Logo

Milvus

Open-source vector database built for billion-scale similarity search

Best for: SMB teams · Mid-market · Enterprise

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What is Milvus?

Milvus is an open-source vector database designed for large-scale similarity search, handling billions of vectors across distributed clusters. It supports multiple index types including HNSW, IVF and DiskANN so teams can trade recall against memory and latency, and offers hybrid search ...

Read more about Milvus

Milvus offers custom pricing plan

turbopuffer - Logo

turbopuffer

Vector and full-text search built directly on object storage

Best for: SMB teams · Mid-market · Enterprise

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What is turbopuffer?

turbopuffer is a search engine that stores indexes on object storage rather than attached disks, which changes the cost profile substantially for large but infrequently queried corpora — you pay storage rates for cold data instead of provisioned memory. It supports vector similarity and ...

Read more about turbopuffer

turbopuffer offers custom pricing plan

Azure AI Search - Logo

Azure AI Search

Managed hybrid search with vector, keyword and semantic ranking

Best for: SMB teams · Mid-market · Enterprise

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What is Azure AI Search?

Azure AI Search combines vector similarity, keyword search and a semantic reranking layer in one managed service, with built-in document cracking and chunking so files can be indexed without a separate ingestion pipeline. It integrates closely with Azure OpenAI for embedding generation and ...

Read more about Azure AI Search

Azure AI Search offers custom pricing plan

Chroma logo

Chroma

Open-source search infrastructure for AI

Best for: SMB teams · Mid-market · Enterprise

Try for Free

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What is Chroma?

Chroma is open-source search infrastructure built for AI applications, supporting vector similarity search, full-text search, regex, and metadata filtering over the same records. It is built on object storage for serverless scalability and is commonly embedded directly into Python or JavaScript ...

Read more about Chroma
Zilliz Cloud logo

Zilliz Cloud

Vector Lakebase for Enterprise AI, Powered by Milvus

Best for: Mid-market · Enterprise

Try for Free

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What is Zilliz Cloud?

Zilliz develops Milvus, an open-source vector database, and offers Zilliz Cloud, a fully managed version built on Milvus. The platform provides real-time vector search, hybrid search, and large-scale data operations for AI workloads such as RAG, semantic search, and recommendation engines, with ...

Read more about Zilliz Cloud

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Learn More About Vector Database Software

Compare 24 vector databases on index type, filtering, scale, hosting model and cost. Covers dedicated engines, Postgres extensions and cloud services.

Vector database software stores and searches high-dimensional embeddings, powering the semantic search, retrieval-augmented generation (RAG), and long-term memory that AI applications depend on. Unlike traditional databases built around exact-match queries, these systems are optimized for approximate nearest-neighbor search at scale, letting an application find the most relevant piece of context out of millions of documents in milliseconds.

  • Whether your existing database can do this, before adding a dedicated engine?
  • Whether metadata filtering happens before or after the vector search, which changes recall and latency?
  • Cost model: provisioned memory versus object storage and per-request billing?

What is vector database software?

Vector database software stores and searches high-dimensional embeddings, powering the semantic search, retrieval-augmented generation (RAG), and long-term memory that AI applications depend on. Unlike traditional databases built around exact-match queries, these systems are optimized for approximate nearest-neighbor search at scale, letting an application find the most relevant piece of context out of millions of documents in milliseconds.

They form a core layer of the modern AI stack alongside the LLM itself and the agent framework calling it.

Vector Database Software compared

Spotsaas lists 24 vector database products. Entries below are ordered by how many verified reviews each carries; where a vendor publishes pricing openly it is shown.

#ProductSpotScoreRatingReviewsStarting price
1
ElasticsearchTop rated
9.84.50204
294.50195
34.301
4
5
6
7
8
9
10

3 of the 24 listings carry verified Spotsaas reviews. Products without reviews are listed but not ranked.

What to check before you buy

Whether your existing database can do this, before adding a dedicated engine

Essential questions to ask the vendor:

  • Whether your existing database can do this, before adding a dedicated engine?

How to overcome it: Check whether your current database already supports vectors before adding a system to operate — for most applications pgvector or Atlas Vector Search is sufficient and removes a synchronization problem.

Whether metadata filtering happens before or after the vector search, which changes recall and latency

Essential questions to ask the vendor:

  • Whether metadata filtering happens before or after the vector search, which changes recall and latency?

How to overcome it: If you do need a dedicated engine, test with your real corpus and your real filters, since pre-filter versus post-filter behavior changes results in ways a generic benchmark will not show.

Cost model: provisioned memory versus object storage and per-request billing

Essential questions to ask the vendor:

  • Cost model: provisioned memory versus object storage and per-request billing?

How to overcome it: Weigh the cost model against your access pattern: an index that is queried rarely does not justify provisioned memory.

Who uses Vector Database Software

Typical roles include Engineers building retrieval-augmented generation over a document corpus, Platform teams choosing between extending Postgres and running a dedicated engine, and Teams running multi-tenant search where most indexes are idle most of the time.

Frequently asked questions

Basics FAQs

What is vector database software?

Vector database software stores and searches high-dimensional embeddings, powering the semantic search, retrieval-augmented generation (RAG), and long-term memory that AI applications depend on. Unlike traditional databases built around exact-match queries, these systems are optimized for approximate nearest-neighbor search at scale, letting an application find the most relevant piece of context out of millions of documents in milliseconds.

Zilliz Cloud · Chroma · Milvus

What does ANN stand for?

ANN stands for approximate nearest neighbor. Vector database software stores and searches high-dimensional embeddings, powering the semantic search, retrieval-augmented generation (RAG), and long-term memory that AI applications depend on. Unlike traditional databases built around exact-match queries, these systems are optimized for approximate nearest-neighbor search at scale, letting an application find the most relevant piece of context out of millions of documents in milliseconds.

Zilliz Cloud · Chroma · Milvus

Pricing FAQs

Is there free vector database software?

Yes. 6 of the 24 products listed offer a genuinely free or freemium tier: Zilliz Cloud, Chroma, Pinecone, Supabase, Rockset, Weaviate. A free trial is not the same thing, and is noted separately on each listing.

Zilliz Cloud · Chroma · Pinecone

Choosing FAQs

How do I choose vector database software?

Check whether your current database already supports vectors before adding a system to operate — for most applications pgvector or Atlas Vector Search is sufficient and removes a synchronization problem. If you do need a dedicated engine, test with your real corpus and your real filters, since pre-filter versus post-filter behavior changes results in ways a generic benchmark will not show. Weigh the cost model against your access pattern: an index that is queried rarely does not justify provisioned memory.

pgvector · Pinecone · Milvus

Buyers FAQs

Who uses vector database software?

Typically engineers building retrieval-augmented generation over a document corpus; platform teams choosing between extending Postgres and running a dedicated engine; teams running multi-tenant search where most indexes are idle most of the time.

Coverage FAQs

How many vector database products does Spotsaas track?

Spotsaas currently lists 24 products in this category, 3 of them with verified reviews. Listings are researched from vendor documentation and updated as the market changes.

Ranking basis: Verified Spotsaas reviews and vendor-published data

Sources: Vendor product documentation and pricing pages, accessed 2026-07-31

Disclaimer: This research has been collated from a variety of authoritative sources. We welcome your feedback at [email protected].