Handle batch, real-time, time-series,
and ad hoc queries with high throughput
and low cost—on-prem or in the cloud.
Over the past decade, CPUs have evolved from having 4–8 cores to featuring over 100 cores. However, memory bandwidth growth hasn't kept up.
As a result, date warehouse providers struggle to improve cost efficiency.
A distributed cache reduces storage requests.
A custom data format enhances data locality.
Adaptive query pipelines handle all operation variants.
Execution strategies are chosen at runtime for optimal performance.
Compressed data and user-space storage caches reduce memory overhead.
Optimized hashmaps and hybrid row/column formats improve data locality.
Temporal access patterns ensure data remains available and isn’t evicted prematurely.
Oxla’s radically vectorized MMP query engine quickly executes queries involving multiple JOINs and GROUP BY operations with minimal CPU usage, reducing compute costs by up to 90% compared to leading data warehouses.
Multi-node architecture
Decoupled storage & compute
High concurrency support
Columnar data storage
Star & snowflake schemas
Optimized data format
Oxla’s radically vectorized MMP query engine quickly executes queries involving multiple JOINs and GROUP BY operations with minimal CPU usage, reducing compute costs by up to 90% compared to leading data warehouses.
Multi-node architecture
Decoupled storage & compute
High concurrency support
Columnar data storage
Star & snowflake schemas
Optimized data format
Real-time data ingestion & processing
Scales for high-velocity data streams
Enables monitoring for anomalies
High availability & fault tolerance
Stores & analyzes sequential data
Advanced time-based aggregations
Supports highly granular data streams
Efficient storage & compression
Oxla's SQL dialect only minimally differs from PostgreSQL, so you can get started right away.
Easily implement Oxla in your data environment with out-of-the-box integrations.
Run queries from BI & observability tools
Stream data in real time for monitoring & live analytics
Ingest ORC, Parquet, JSON and CSV files from object storage
Orchestrate ingestion using Spark & Airflow
Run queries using native language libraries
Build your own integrations and custom pipelines
Install Oxla for Linux using Docker and connect with PostgreSQL client to experience the efficiency of a single node on your machine.