Back in 2018, when I was at Greenplum, my team worked through The Internals of PostgreSQL together alongside Andy Pavlo’s CMU database courses. It was invaluable for anyone working on the database kernel. Today, a beginner can get that same interactive learning experience simply by chatting with AI, much like the discussions our team had back then.
Now I’m building Lavik, a new cache service for PostgreSQL. Traditional caches like Redis are DRAM-based, so they can only hold a small slice of hot data. Once your data outgrows memory, you’re exposed to cache miss storms, where a flood of requests falls through to PostgreSQL all at once. Nobody likes those. (OpenAI encounter the similar cache miss storms problem: https://openai.com/index/scaling-postgresql/)
Lavik takes a different path: it runs on NVMe SSDs, and it’s still faster than Redis running on DRAM. That’s not what most people expect. Conventional wisdom says SSD-based systems trade speed for capacity, but Lavik gives you both. You can keep TB-scale data in cache while getting 1M QPS and sub-millisecond P99 latency.
Now I’m building Lavik, a new cache service for PostgreSQL. Traditional caches like Redis are DRAM-based, so they can only hold a small slice of hot data. Once your data outgrows memory, you’re exposed to cache miss storms, where a flood of requests falls through to PostgreSQL all at once. Nobody likes those. (OpenAI encounter the similar cache miss storms problem: https://openai.com/index/scaling-postgresql/)
Lavik takes a different path: it runs on NVMe SSDs, and it’s still faster than Redis running on DRAM. That’s not what most people expect. Conventional wisdom says SSD-based systems trade speed for capacity, but Lavik gives you both. You can keep TB-scale data in cache while getting 1M QPS and sub-millisecond P99 latency.
Lavik is open source under the Apache License. GitHub: https://github.com/eloqdata/lavik Website: https://lavik.dev