Serverless Vector Search
Sneller’s serverless vector search eliminates the need for capacity planning and expensive migrations.
Sneller’s serverless vector search eliminates the need for capacity planning and expensive migrations.
Learn how Sneller makes it easy to perform semantic search using SQL for AI-powered applications.
Learn how we “eat our own dogfood” by using Sneller SQL to monitor Sneller Cloud.
Sneller automatically uses a lightweight sparse index to index timestamp values in your data. Our timestamp sparse index lets us accelerate queries without introducing meaningful overhead during ingestion or query planning.
Learn how Sneller is able to achieve the advantages of columnar database compression on row-oriented, schemaless data.
One of Sneller’s novel features is a bytecode-based virtual machine written almost entirely in AVX-512 assembly. While Sneller is far from the first project to incorporate SIMD acceleration into a query engine, our interpreter is unusual in that it is implemented entirely in assembly.
JSON has become one of the most common data interchange formats. It’s challenging to store JSON in traditional column-based database engines, so we decided to implement a schemaless engine to fully support JSON.