Self-hosted open-source vector database in Developer Backend & Vector Search Services | Parse

For an on-premise deployment focused on data privacy, Qdrant is the top recommendation. It strikes the ideal balance between being straightforward to deploy via a single Docker container and offering robust, production-grade horizontal scaling.

The best open-source options for on-premise setups depend on your specific scale and infrastructure:

Qdrant (Best Overall for On-Premise)
- Why it fits: Written in Rust, it is exceptionally resource-efficient and fast. It features powerful payload-based filtering (critical for metadata filtering during searches) and native support for distributed sharding.
- Ease of deployment: Extremely simple to spin up using a standard Docker image or Kubernetes chart. It doesn't require a complex multi-service ecosystem to get started.
- Scaling: Scales smoothly from a single-node development setup to a distributed cluster.
pgvector (PostgreSQL Extension) (Best if you already use Postgres)
- Why it fits: If your enterprise already runs PostgreSQL on-premise, adding pgvector keeps your data inside a familiar, heavily audited relational database without adding a new standalone database to your infrastructure.
- Ease of deployment: As simple as running CREATE EXTENSION vector; on your existing Postgres instance.
- Scaling: Perfect for small-to-medium workloads (up to tens of millions of vectors), but scaling out distributed reads/writes becomes harder than with a purpose-built distributed vector database.
Milvus (Best for Massive, Billion-Scale Data)
- Why it fits: If your privacy requirements involve massive data scale (hundreds of millions to billions of vectors), Milvus is architected specifically for extreme distributed scale.
- Ease of deployment: Heavier to manage. While it has a standalone Docker mode for smaller footprints, true scaling relies on a decoupled microservices architecture typically deployed via Helm/Kubernetes.

To help narrow down the exact fit, tell me:

Roughly how many vectors (documents/records) do you plan to store initially and long-term?
Is your on-premise infrastructure standardized on Docker/Swarm or Kubernetes?

Self-hosted open-source vector database

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Best open-source vector databases for on-premise deployment

Top 4 options

1. Qdrant

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2. Milvus

3. Weaviate

4. Chroma

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