AresDB is a GPU-based real-time analytics storage and query engine with low memory overhead, real-time upserts with primary key deduplication, and time series aggregations on both streaming and finite dimensional data.
Developed by Uber to meet their specific need "to make similar queries over relatively small, yet highly valuable, subsets of data (with maximum data freshness) at high QPS and low latency," with queries such as time series aggregations over geofences.
Uses a proprietary execution language called Ares Query Language (AQL) which is based in the JSON format.
AresDB works with vector batches that are efficiently processed in parallel using the Thrust library.
Data within the archival delay of a table is kept uncompressed in live batches, while everything else is stored in compressed archival batches. If new data is ingested that is outside the archival array, it's added to an archival backfill queue which will be inserted into the archived batches asynchronously.
The CPU is only used to load information from storage into CPU memory and to distribute this data to GPU memory. The database system delegates each operator in a query to some GPU, so it's able to handle multiple GPUs by delegating different operations to different GPUs, each of which have completely separate memory. There are plans to implement proper distributed designs, but currently we're limited to a single system with multiple GPUs.
Executes queries with the one operation per kernel (OOPK) model.