Blog

Serverless Vector Search

Sneller’s serverless vector search eliminates the need for capacity planning and expensive migrations.

continue reading...

1 Billion Records on Grafana

See how Sneller powers a Grafana dashboard with 1 billion records from the GitHub archive data.

continue reading...

Semantic Search with SQL

Learn how Sneller makes it easy to perform semantic search using SQL for AI-powered applications.

continue reading...

How Sneller Cloud Runs on Itself

Learn how we “eat our own dogfood” by using Sneller SQL to monitor Sneller Cloud.

continue reading...

64-bit Integer Division with AVX-512

Integer division is an arithmetic operation that is not provided natively by SIMD instruction set extensions. In this article we provide a vectorized solution to successfully divide signed 64-bit integers by taking advantage of AVX-512

continue reading...

Introducing Iguana: extremely fast SIMD-optimized decompression

Sneller relies on a custom vectorized compression algorithm to enable extreme decompression speeds.

continue reading...

Branchless Code With AVX-512

Sneller uses 16 parallel data lanes for almost all tasks, including loading and decompressing data, all without the use of branches. We heavily rely on predicated instruction execution provided by the AVX-512 instruction set to achieve this. In this post, we will explain a simple example of converting a string to uppercase, which is frequently used in our string processing functions.

continue reading...

Accelerating Fuzzy Search using AVX-512

We present our SQL fuzzy string compare and contains functionality that allows multi GiB/s processing without any need for preprocessing or indexing. Yes, that is right, fuzzy functionality yet no planning needed!

continue reading...

Sneller: Querying terabytes of JSON per second

Learn how Sneller is capable of querying terabytes of JSON per second on medium sized clusters.

continue reading...

Sneller Regex vs Ripgrep

We present a speed comparison between ripgrep and Sneller’s SQL regular expression engine. We conclude that Sneller is faster with large text files, thanks to its ability to leverage multi-threading and optimized hardware utilization, despite the performance penalty for decompressing data.

continue reading...