BlazingSQL
BlazingSQL is a distributed GPU-accelerated SQL engine with data-lake integration for e.g. Apache Arrow, Apache Parquet. It is ACID-compliant. BlazingSQL targets ETL workloads and aims to perform efficient read IO and OLAP querying. BlazingDB refers to the company and BlazingSQL refers to the product. It is currently under active development with 15 employees that have offices in San Franscisco and Peru.
History
BlazingSQL started as a GPU table joiner for multi-terabyte databases. The Aramburu brothers, Rodrigo and Felipe, founded a company in 2013 that provided analytical solutions and needed to speed up joins for pension fraud detection. The system is closed-source with a free community binary. It integrates with the open-source open GPU data science initiative, RAPIDS, which relies on NVIDIA GPUs.
Compression
Dictionary Encoding Delta Encoding Run-Length Encoding Bit Packing / Mostly Encoding
BlazingSQL supports compressing and decompressing directly on the GPU. It accepts a variety of input formats such as Apache Parquet, BlazingDB Simpatico (GPU-compressed distributed files), and GDF (GPU dataframes built on Apache Arrow). Data is then sent to the GPU compressed. It is able to operate directly on compressed data.
- https://blazingdb.atlassian.net/wiki/spaces/BlazPub/overview
- https://news.ycombinator.com/item?id=15840900
- https://www.nvidia.com/content/dam/en-zz/Solutions/data-analytics/documents/nvidia-dgx-analytics-blazing-db-solution-brief-r3-web.pdf
- https://news.ycombinator.com/item?id=15820091
- https://news.ycombinator.com/item?id=12485967
Storage Model
Decomposition Storage Model (Columnar)
BlazingSQL is a column-store. To execute a query, it compresses and transmits relevant columns to the GPU. On the GPU, data is represented as a GPU DataFrame (GDF). GDFs are built on top of Apache Arrow, which is a columnar in-memory format.
Concurrency Control
Multi-version Concurrency Control (MVCC)
BlazingSQL supports snapshot isolation, which is most likely achieved with MVCC.
