Adrien’s blog

Common wisdom is that databases should make decisions at the query planning stage and then hand over the plan to a dumb executor.

I was recently chatting with a friend about database architecture, and why, for instance, OLTP databases and search engines are implemented very differently.

In a previous blog post, I explained how Lucene significantly improved query evaluation efficiency by migrating to a vectorized execution model, and described the algorithm that Lucene uses to evaluate conjunctive queries.

Virtual function calls are quite expensive, which is why database systems have been looking into ways to avoid performing one or more virtual function calls per record when processing a query.

Some time ago, I wrote that “if you do not configure an index sort on your Lucene indexes, you are missing search-time efficiency benefits that are almost certainly worth the (low) index-time overhead”.

In a previous post, I took a look at the Vespa vs.

I was attending Berlin Buzzwords today and someone asked me about the Elasticsearch vs.

“Search Benchmark, the Game” is maintained at https://github.com/quickwit-oss/search-benchmark-game by the Tantivy folks and published at https://tantivy-search.github.io/bench/.

EDIT (2025-11-12): Thanks to learnings from the Tantivy project, as of version 10.3, Apache Lucene is now on par with Tantivy on most queries and even faster on some queries.