Pgvector vs TiDB

Pgvector vs. TiDB

Compare Pgvector vs. TiDB by the following set of capabilities. We want you to choose the best database for you, even if it’s not us.

Pgvector vs. TiDB on Scalability

PgvectorTiDB

Separation of storage and compute

Yes. pgvector enables separation of storage and compute by allowing you to store your application data on one database while storing vectors, lookup values, and filter values on a separate database.

❌

Separation of query and insertions

❌

Yes.

Multi-replication

✔️

❌

Dynamic segment placement vs. static data sharding

❌

Both

Cloud-native

❌

Billion-scale vector support

❌

pgvector scalability

You can use a solution like YugaByteDB to extend the capabilities of Postgres for distributed environments.

TiDB

TiDB is designed with scalability as one of its core features. It offers both horizontal and vertical scaling capabilities to handle growing workloads and data volumes.

Pgvector vs. TiDB on Functionality

Performance is the biggest challenge with vector databases as the number of unstructured data elements stored in a vector database grows into hundreds of millions or billions, and horizontal scaling across multiple nodes becomes paramount.

Furthermore, differences in insert rate, query rate, and underlying hardware may result in different application needs, making overall system tunability a mandatory feature for vector databases.

PgvectorTiDB

Role-based Access Control (RBAC)

✔️

❌

Disk Index support

❌

Hybrid Search (ie Scalar filtering)

Yes. Sparse & Dense Vectors and Scalar filtering.

Yes, vector search & SQL search

Partitions/namespaces/logical groups

❌

Index type supported

HNSW & IVFFlat

HNSW

Multiple in-memory indexes support

❌

No. HNSW only

TiDB

TiDB offers vector search through its serverless cluster and supports vectors with a maximum dimension of 16,000. The Vector data type in TiDB is designed to store single-precision floating-point numbers (Float32). It only supports cosine distance and L2 distance for similarity measurement.

Pgvector vs. TiDB on Purpose-built

PgvectorTiDB

Purpose-built for Vectors

pgvector is an add-on to Postgres

No, vector search is an add-on to TiDB Cloud serverless.

Tunable consistency

✔️

❌

Support for both stream and batch of vector data

✔️

❌

Binary Vector support

❌

Multi-language SDK

Use pgvector from any language with a Postgres client

No. TiDB does not provide specific SDKs. Instead, it is designed to be compatible with MySQL, which means TiDB can be used with any language with MySQL client or driver support.

Database rollback

✔️

❌

Pgvector vs. TiDB: what’s right for me?

Pgvector

pgvector is a PostgreSQL extension designed to facilitate the storage, querying, and indexing of vectors within a PostgreSQL database.

License: PostgreSQL License

TiDB

TiDB is an open-source distributed SQL database for OLAP and OLTP workloads. It now offers a vector search capability (in public beta) as an add-on to its SaaS solution, TiDB Cloud Serverless.

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