SQLite WAL still has one writer
In short: SQLite WAL allows readers alongside a writer, but agent throughput still depends on short write transactions and explicit stale-state checks.
↗SQLite — Isolation and write-ahead loggingSQLite's write-ahead log arrived in version 3.7.0 on 22 July 2010. It lets readers continue while a writer commits. It did not turn SQLite into a database with many simultaneous writers.
That distinction is why I keep returning to the SQLite isolation guide. SQLite WAL still has one writer. If an agent pool spends most of its time reading but occasionally holds a write transaction across a model call, reader concurrency is the wrong capacity number to celebrate.
SQLite WAL separates readers from the writer
The documentation explains snapshot isolation in WAL mode: readers retain a view of the database while committed changes accumulate separately. The WAL guide also describes checkpointing and the constraint that only one writer can append at a time.
Read those two guides together before copying a database tuning recipe. They describe a coordination contract, not a promise that increasing worker count will increase completed writes.
Keep model calls outside the write transaction
For a hypothetical local agent service, I would separate reasoning from the transaction that records its result. Read the relevant state, release the connection's transaction, do the expensive work, then open a short transaction to validate the state and commit the intended change.
The validation step matters. Releasing a transaction creates room for another worker to change the record. A version check or conditional update must decide whether the reasoning still applies. Moving inference outside the transaction without that check simply trades contention for stale writes.
My first measurement would be writer occupancy: how long each transaction owns the scarce write opportunity, and what it is doing during that interval. A waiting remote model call should be visible as a design choice, not disappear inside a database-latency average.
This is an architectural recommendation, not a benchmark. WAL also has deployment constraints, including its shared-memory requirements; the documentation does not make arbitrary network filesystems a safe home for it.
What's in it for you
- Inspect transaction duration before adding agent workers.
- Make stale-state rejection explicit when reasoning happens outside a transaction.
WAL makes reading alongside writing practical; your transaction boundary still decides who waits.
