Query Interface

Custom API

Uses a proprietary execution language called Ares Query Language (AQL) which is based in the JSON format.

Joins

Hash Join

Supports hash joins from fact tables (finite set data such as cities) to dimension tables (infinite streaming data such as rides). Also supports geospatial joins (i.e. geographically bounded area overlap)

Storage Model

Decomposition Storage Model (Columnar)

Compression

Run-Length Encoding

Logging

Logical Logging

Log files contain description of database upserts which must be replayed to rebuild the database after a crash.

Storage Architecture

Hybrid

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.

Data Model

Relational

Hardware Acceleration

GPU

Parallel Execution

Intra-Operator (Horizontal)

Executes queries with the one operation per kernel (OOPK) model.

System Architecture

Shared-Disk

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.

Query Execution

Vectorized Model

AresDB works with vector batches that are efficiently processed in parallel using the Thrust library.