Scale your self-hosted analytical
data platform
Purpose-built for compute, memory, and storage efficiency, Oxla is a self-hosted OLAP database optimized for large-scale, low-latency analytics with robust time-series support.
Purpose-built for compute, memory, and storage efficiency, Oxla is a self-hosted OLAP database optimized for large-scale, low-latency analytics with robust time-series support.
Designed from the ground up for performance at scale, Oxla’s radically vectorized MPP query engine executes compute-intensive queries with minimal CPU and RAM overhead, enabling low-latency analytics across diverse workloads.
Get cloud-native performance to handle growing data volumes without scaling your infra. Simple, capacity-based pricing means total predictability.
Deploy and maintain nodes easily using Docker and a clean, human-readable YAML config. No ops-heavy setup required.
Scale storage and compute independently, and keep it simple with S3-compatible storage like MinIO.
Growing datasets cease to be a growing problem with 77x more cost-efficient storage than MS SQL Server.
Plug Oxla into your stack with built-in connectors.
As the first investor, I placed my bets on Oxla’s radical approach to performance in the competitive data warehouse space. 4 years later I’m beyond impressed by the team’s hard work building an OLAP DBMS that leverages modern hardware capabilities.
As the first investor, I placed my bets on Oxla’s radical approach to performance in the competitive data warehouse space. 4 years later I’m beyond impressed by the team’s hard work building an OLAP DBMS that leverages modern hardware capabilities.
As the first investor, I placed my bets on Oxla’s radical approach to performance in the competitive OLAP space. 5 years later I’m beyond impressed by the team’s hard work building a modern, self-hosted C++ SQL query engine.
