The exact concerns we hear in every initial conversation — answered up front so you don't have to chase them.
GET, SET, DEL, HGET-style commands, swap the connection string and you're running. If you rely on range scans, secondary indexes, or full-text search, VeltrixDB is the wrong tool — we'll tell you that in the demo.io_uring SQPOLL eliminates syscalls on the hot path, a 256 GB LIRS cache absorbs ~94% of reads, and key-value separation means compaction never touches the values — so background work never competes with your user requests for NVMe bandwidth.Every claim on this page has a benchmark, a paper, or a config file behind it. Go deep before you commit.
Hardware specs, workload generator config, percentile distributions, and replayable harness. 32 pages.
Architecture deep-diveHow the VLog, io_uring, and LIRS cache combine to keep P99 stable at any write load.
Migration guideShadow reads, dual-write strategy, cutover checklist, and rollback plan — with copy-pasteable Terraform.
Comparison guideP99 latency, storage cost, write amplification, and the GC death spiral Redis can't fully solve. With migration code.
One email. The full methodology, raw P99 distributions, and a side-by-side cost analysis vs DynamoDB, Redis Enterprise, and Cassandra at 1B keys.
VeltrixDB started the night a flash sale buried our Redis cluster under 8 GB of session state. The on-call channel filled with screenshots of P99 climbing past 400 ms. The bill that quarter was already 3× what we'd budgeted.
We tried every workaround you've tried — read replicas, write batching, a DynamoDB migration that ended with a quarter of unpredictable per-op billing. None of it solved the actual problem.
The real problem was that every popular database rewrites your values during compaction. It's a 10× amplification tax on storage and a guaranteed spike in tail latency exactly when you can least afford it.
So we built VeltrixDB the way we wished a database had been built when we were on call: key–value separation so compaction never touches values, io_uring so the kernel never gets in the way, and fixed cluster pricing so the bill never surprises you.
Now we ship it to teams who recognise their own war stories in ours.