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 Postgres — pgvector
- Best managed dedicated engine — Pinecone
- Best open-source at scale — Milvus
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.
Showing 1-20 out of 24
9.8
SpotScore

Elasticsearch
Empower your website with intelligent search capabilities.
Best for: SMB teams · Mid-market · Enterprise
Add to compare
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 ElasticsearchElasticsearch offers custom pricing plan
9.0
SpotScore
Weaviate
Open-source vector database for semantic search, RAG, and AI-native applications
Best for: SMB teams
Add to compare
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 WeaviateStarts 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.
7.6
SpotScore

SingleStore
Efficiently organize and grow your business.
Best for: SMB teams · Mid-market · Enterprise
Add to compare
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, ...
Read more about SingleStoreSingleStore offers custom pricing plan

- Shortlisted in minutes, not days
- Matched to your business
- Trusted by 2M+ software buyers every year
Step 1 of 4
How big is your team?
We tailor recommendations to companies your size.
Typesense
Open-source search engine with vector and hybrid search
Best for: SMB teams · Mid-market · Enterprise
Add to compare
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 — ...
Read more about TypesenseTypesense offers custom pricing plan
Deep Lake
Database for AI storing vectors alongside raw multimodal data
Best for: SMB teams · Mid-market · Enterprise
Add to compare
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 ...
Read more about Deep LakeDeep Lake offers custom pricing plan
pgvector
Vector similarity search as a PostgreSQL extension
Best for: SMB teams · Mid-market · Enterprise
Add to compare
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 ...
Read more about pgvectorpgvector offers custom pricing plan
Meilisearch
Developer-friendly search with hybrid keyword and vector retrieval
Best for: SMB teams · Mid-market · Enterprise
Add to compare
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 ...
Read more about MeilisearchMeilisearch offers custom pricing plan
Vespa
Search and recommendation engine with native vector and tensor support
Best for: SMB teams · Mid-market · Enterprise
Add to compare
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 ...
Read more about VespaVespa offers custom pricing plan
ClickHouse
Columnar OLAP database with vector similarity functions
Best for: SMB teams · Mid-market · Enterprise
Add to compare
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, ...
Read more about ClickHouseClickHouse offers custom pricing plan
Upstash Vector
Serverless vector database priced per request
Best for: SMB teams · Mid-market · Enterprise
Add to compare
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 ...
Read more about Upstash VectorUpstash Vector offers custom pricing plan
LanceDB
Embedded multimodal vector database on the Lance columnar format
Best for: SMB teams · Mid-market · Enterprise
Add to compare
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 ...
Read more about LanceDBLanceDB offers custom pricing plan
Redis
In-memory data store with vector similarity search
Best for: SMB teams · Mid-market · Enterprise
Add to compare
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 ...
Read more about RedisRedis offers custom pricing plan
Vertex AI Vector Search
Google Cloud managed vector search at very large scale
Best for: SMB teams · Mid-market · Enterprise
Add to compare
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 SearchVertex AI Vector Search offers custom pricing plan
Add to compare
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 ...
Read more about MarqoMarqo offers custom pricing plan
MongoDB Atlas Vector Search
Vector search inside the MongoDB Atlas document database
Best for: SMB teams · Mid-market · Enterprise
Add to compare
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 SearchMongoDB Atlas Vector Search offers custom pricing plan
Milvus
Open-source vector database built for billion-scale similarity search
Best for: SMB teams · Mid-market · Enterprise
Add to compare
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 MilvusMilvus offers custom pricing plan
turbopuffer
Vector and full-text search built directly on object storage
Best for: SMB teams · Mid-market · Enterprise
Add to compare
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 turbopufferturbopuffer offers custom pricing plan
Azure AI Search
Managed hybrid search with vector, keyword and semantic ranking
Best for: SMB teams · Mid-market · Enterprise
Add to compare
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 SearchAzure AI Search offers custom pricing plan
Add to compare
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
Add to compare
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 CloudLearn 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.
| # | Product | SpotScore | Rating | Reviews | Starting price |
|---|---|---|---|---|---|
| 1 | ElasticsearchTop rated | 9.8 | ★★★★★4.50 | 204 | — |
| 2 | 9 | ★★★★★4.50 | 195 | — | |
| 3 | — | ★★★★★4.30 | 1 | — | |
| 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.
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.
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.





