What Infino is good at
- Fast warm queries. On a 1-million-document index, a warm single-term BM25 query returns in the microsecond range. Once a query’s byte ranges are cached, search runs from local memory.
- Multi-modal retrieval over one copy. BM25 full-text, vector search, and SQL run over the same rows, and the search functions compose into SQL plans, so there’s no second system to sync and no client-side result stitching.
- Flat storage economics. Data lives in object storage at object-storage prices, as standard Parquet, with no replication factor multiplying the footprint and no always-on storage tier to pay for between queries.
- Light operational surface. It runs in-process as a library, so there’s no separate cluster to provision or keep warm.
What Infino is not (yet) the right tool for
- Cold first-touch latency. Object storage has high first-byte latency, so the first query to touch a file pays an object-store round trip (hundreds of milliseconds) before its bytes are cached. Infino prunes aggressively to minimise what it fetches, but if your workload is dominated by one-shot queries against never-before-touched data, that round trip is real. Warm and repeated queries do not pay it.
- Bulk-ingest throughput is solid, not the headline. Building indexes and committing to object storage is parallel and respectable (a 1M-document index builds in a couple of seconds in memory, ~470K docs/s with parallel writers), but ingest is not where Infino’s biggest advantage is. Query latency is. If your workload is write-dominated rather than read-dominated, weigh that.
- Not a transactional database. Writes are append-only with an atomic commit as the durability boundary; updates and deletes go through tombstones, not in-place row mutation. Infino is built for retrieval over largely append-only corpora, not high-rate row-level OLTP.
- No wire protocol yet. Infino is embedded: you reach it as a library from your own process. There is no server endpoint for external SQL clients to attach to.
benches/README.md.
See also
- Object-storage-native retrieval: the model and why it makes these tradeoffs.
- Architecture overview: where Infino fits best.