Oxla is a high-performance analytical database built to maximize data processing efficiency.

As data production continues to grow exponentially, leading data warehouses like Snowflake, Databricks, and BigQuery have become prohibitively expensive for processing terabytes of data due to performance inefficiencies. This is largely because they rely on outdated technology that fails to leverage modern hardware capabilities.

The main challenge stems from a disparity: while core counts have increased more than twenty-fold in the past decade, data transfer between RAM and the CPU has slowed by three-fold per CPU clock tick, creating a performance bottleneck.

Oxla addresses this bottleneck by deploying an innovative parallelized query engine that optimises data transfer between CPU and RAM. The result is a substantial performance boost, yielding up to 90% reduction in compute costs.

By making distributed analytics affordable, we aim to empower companies facing rising data processing costs, unlock previously cost-prohibitive use cases, and democratize data science.

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Kacper Szcześniak

Wojciech Chlapek

Konrad Sopala

Ian Owczarek

Jacek Szlendak

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