Hi ziadalharash,
Regarding vector indexes: unfortunately, they are not available in Forge SQL at the moment.
TiDB’s vector search indexes (HNSW) rely on TiFlash replicas. According to the TiDB documentation, the vector search index feature requires TiFlash. Since TiFlash is not available in Forge SQL, HNSW vector indexes cannot currently be used there.
The example from my post therefore performs exact vector similarity search without a vector index.
One important detail is that Forge SQL data is isolated per tenant. This means the full scan is limited to the data of a single tenant rather than all installations of the app. For many tenants this may be perfectly acceptable, while tenants with significantly larger vector datasets could eventually experience performance degradation.
This is something that can be detected rather than guessed upfront. For example, using the SQL observability approach I described in my other post, we can track database execution time per resolver/tenant and identify when vector search starts becoming expensive. Slow queries can then be investigated further using their execution plans.
If this becomes a problem for a particular workload, the next step would be to reduce the candidate set before applying vector similarity - for example, by logically partitioning the searchable data or introducing additional application-level filtering instead of running VEC_COSINE_DISTANCE() against every vector in the tenant’s table.
I also created a Forge feature request for this:
FRGE-2141 — Native Vector Search Support in Forge SQL
The goal is to have native vector functionality officially supported and documented by Atlassian, so developers can rely on it rather than depending on an undocumented capability of the underlying TiDB implementation.
So, at the moment, I would summarize it as:
VECTORcolumns - work in Forge SQLVEC_COSINE_DISTANCE()/ vector similarity functions - work- Vector indexes - not available because they depend on TiFlash
- Official Forge SQL support/guarantees for vector functionality - this is what still needs clarification from Atlassian
Hopefully Atlassian can clarify the support status here, especially whether the currently working vector functionality can be safely relied upon for production apps.