Overview
Blnk is optimized out of the box for most workloads. This guide is for teams processing millions of records who want to squeeze out extra performance when searching directly from the DB.Default indexes
These fields are already indexed and optimized:| Table | Indexed fields |
|---|---|
transactions | transaction_id, reference, status, currency, source, destination, parent_transaction, created_at, meta_data (GIN) |
balances | balance_id, ledger_id, identity_id, indicator, currency, created_at |
ledgers | ledger_id, created_at |
identity | identity_id, country, created_at |
accounts | account_id, ledger_id, identity_id, balance_id, created_at |
Use Typesense for large-scale queries
For complex searches, filtering across millions of records, or when you need sub-millisecond response times, use Blnk’s Typesense integration instead of database queries. Typesense is optimized for:- Full-text search across any field
- Faceted filtering with instant results
- Sorting large datasets without custom indexes
See Search via Typesense docs for more.
Adding custom indexes
If you’re not using Typesense and frequently sort or filter by a specific field at scale, add an index.Create composite indexes
For queries that filter and sort on multiple fields, composite indexes are more efficient:
Debugging slow queries
UseEXPLAIN ANALYZE to see how Postgres executes a query:
Seq Scanon large tables: strong signal you need an index- High actual time values: indicates slow query execution
- Large row counts being filtered down late: suggests missing indexes
Example Output
status would improve performance.
Best practices
-
Monitor query performance: Use
EXPLAIN ANALYZEregularly to identify slow queries. - Index strategically: Only add indexes for fields you filter or sort on frequently. Too many indexes can slow down writes.
- Use composite indexes: When filtering and sorting on multiple fields together, create composite indexes.
- Consider Typesense: For complex queries or very large datasets, Typesense often provides better performance than database indexes.
- Test in production-like environments: Index performance can vary based on data distribution and query patterns.