Vector Search + MySQL

Serverless MySQL Vector Search

TiDB Cloud Zero combines MySQL compatibility with vector search and full-text search, which makes it useful for early RAG systems, semantic retrieval experiments, and AI application demos that still need SQL structure.

MySQL-compatible database for structured app data. Vector search and full-text search on the same platform. Good for RAG prototypes, retrieval experiments, and evaluation setups. Disposable first, claimable later.

Home / Use Cases / Serverless MySQL Vector Search

Why this page exists

Teams searching for serverless MySQL vector search or RAG MySQL database usually want to avoid splitting one early product into several services too soon.

TiDB Cloud Zero is useful when the experiment needs SQL tables, embeddings, and text retrieval but the team still wants the shortest path from idea to running system.

Vector search plus full-text search matters

Semantic retrieval is helpful when intent matters more than exact words. Full-text search is still valuable when keyword precision, lexical matching, or explainability matters.

Putting both in the same MySQL-compatible environment keeps the prototype simpler and reduces glue code during the evaluation phase.

RAG and retrieval experiments
Semantic search over application data
Keyword and fuzzy search in one stack
Early AI features before permanent infrastructure decisions

Search intent covered here

This page addresses searches like serverless MySQL vector database, MySQL vector search, MySQL full-text search, and RAG MySQL database.

Provision a disposable database for search and RAG experiments

This example keeps the flow simple: create a database, export the connection string, and start using it with standard MySQL tooling.

curl -s -X POST https://zero.tidbapi.com/v1beta1/instances \
  -H "Content-Type: application/json" \
  -d '{"tag":"vector-search"}' \
  | tee tidb-zero.json

export TIDB_CONNECTION_STRING="$(jq -r '.instance.connectionString' tidb-zero.json)"

mysql "$TIDB_CONNECTION_STRING" -e "SELECT 1 AS ready_for_rag;"

Related Paths

Keep the site graph tight. Each page answers a different question and links to the next most relevant topic.

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FAQ

Can I use TiDB Cloud Zero for RAG prototypes?

Yes. It is a good fit for early retrieval experiments where you want SQL data plus vector and text search without provisioning long-lived infrastructure first.

Is it only for embeddings?

No. The point is that you can keep relational application data in the same MySQL-compatible database instead of splitting the prototype too early.

Does it replace a permanent production search stack?

No. Zero is disposable by design. If the experiment proves out, claim the instance or move the architecture into a longer-lived TiDB Cloud environment.