16 karma · joined January 30, 2026
Using an LLM to polish grammar vs. having it generate opinions wholesale are different things.
When you repeat the same thing over and over you naturally end up with a tight version of it. That's not an LLM, that's just how it works when you talk about something a lot.
And honestly even if I did use an LLM to write a comment on HN, so what? The code is what matters.
Go run the benchmarks, read the source, open an issue if something breaks.
That's the part that actually counts.
The SQL-as-queue pattern is definitely underrated. Great to hear it worked well at that scale.
Current state: bunqueue is single-server with SQLite persistence.
If the server goes down for 5 minutes, clients cannot push/pull during that window. However: the client SDK has automatic reconnection with exponential backoff + jitter, all data is safe on disk (SQLite WAL mode), and on restart active jobs are detected as stalled and re-queued automatically. Delayed/scheduled jobs resume from their run_at timestamps.
For your use case (100k+ scheduled jobs, low throughput): well-optimized. We use MinHeap + SQLite indexes for O(k) refresh where k = jobs becoming ready, not O(n) scan.
What bunqueue does NOT have today: no clustering, no multi-instance with shared state, no automatic failover, no replication.
What it does have: S3 automated backups (compressed, checksummed) for disaster recovery. A "durable: true" option for zero data loss on critical jobs. Zero external dependencies.
Roadmap: HA is something we're actively working toward. Native HA with leader election and replication. Managed cloud offering with automatic failover and geographic distribution.
Bottom line: if you need true HA today, BullMQ + Redis Sentinel/Cluster is the safer choice. bunqueue is for when you want simplicity, high performance (~100k jobs/sec), and can tolerate brief downtime with automatic recovery.
The idea: for single-server deployments, SQLite can handle 100k+ ops/sec with WAL mode, so why add infrastructure?
Two modes:
- Embedded: everything in-process, just `import` and go
- Server: run `bunqueue start`, connect multiple workers via TCP
Features: priorities, delays, retries, cron jobs, DLQ, job dependencies, BullMQ-compatible API. Trade-offs vs Redis:
- Not for multi-region distributed systems
- Best for single server or small clusters
Happy to answer any questions about the architecture!Some numbers from my M1 Max:
1.2M+ ops/sec for batch push 494K ops/sec processing with 16 workers 1 million jobs in under 3 seconds with 100% data integrity
It supports delayed jobs, retries, priorities, and concurrent workers. The repo includes a full benchmark suite if you want to test on your own hardware. Would love feedback on the API or any features you'd find useful.