BlazingSQL

BlazingSQL is a distributed GPU-accelerated SQL engine with data-lake integration. 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. BlazingDB has 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.

Storage Model

Decomposition Storage Model (Columnar)

BlazingSQL does not write data. It reads compressed data directly from the data lake 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.

Views

Virtual Views Materialized Views

BlazingSQL supports both virtual and materialized views. Materialized views are currently not persistent.

Storage Architecture

Hybrid

BlazingSQL loads data to disk, but ultimately operates on the data in GPU.

Query Execution

Vectorized Model

BlazingSQL operations are vectorized on the GPU (SIMD).

Query Interface

SQL

BlazingSQL exposes a Python connector for executing SQL commands.

Concurrency Control

Not Supported

BlazingSQL does not write data. It reads directly from the data lake, loading it into GPU data frames that can be shared with interprocess communication. BlazingSQL handles concurrency for the generation of result sets. The user is responsible for ensuring that the data is in a good state when it is queried.

Data Model

Relational

BlazingSQL is a relational database. It accepts multiple in-memory formats (e.g. Apache Parquet) and provides a SQL interface for querying the data.

System Architecture

Shared-Nothing

BlazingSQL worker nodes push information to each other whenever required. There is a notion of a distributed cache, and nodes can ask each other for cached data-lake data.

Logging

Physical Logging

When importing data, BlazingSQL always writes it to disk, compresses it and has it in a query-ready state.

Query Compilation

Not Supported

BlazingSQL does not appear to currently do query compilation.

Storage Organization

Log-structured

BlazingSQL appears to be log-structured.

Joins

Hash Join

BlazingSQL supports transformations and hash joins (left, left-outer, full-outer) on all the column types supported by rapids.ai.

Hardware Acceleration

GPU

BlazingSQL is hardware-accelerated with NVIDIA GPUs. Relevant columnar data is compressed, cached and sent to the GPU. The GPUs are used to speed up transforms, predicates, running predicates while skipping metadata, and to perform accelerated joins.

Indexes

Not Supported

BlazingSQL does not appear to support indexes.

Stored Procedures

Not Supported

As of BlazingSQL 1.3, stored procedures do not appear to be supported.

BlazingSQL Logo
Website

https://blazingdb.com/

Tech Docs

https://docs.blazingdb.com/

Developer

BlazingDB

Country of Origin

PE

Start Year

2015

Project Type

Commercial

Written in

C++

Supported languages

SQL

Operating Systems

Linux

Licenses

Proprietary