BlazingSQL is a GPU accelerated SQL engine built on top of the RAPIDS ecosystem. RAPIDS is based on the Apache Arrow columnar memory format, and cuDF is a GPU DataFrame library for loading, joining, aggregating, filtering, and otherwise manipulating data.
BlazingSQL is a SQL interface for cuDF, with various features to support large scale data science workflows and enterprise datasets.
- Query Data Stored Externally - a single line of code can register remote storage solutions, such as Amazon S3.
- Simple SQL - incredibly easy to use, run a SQL query and the results are GPU DataFrames (GDFs).
- Interoperable - GDFs are immediately accessible to any RAPIDS library for data science workloads.


Forget about schema management, preprocessing, and loading — run SQL directly on files or GPU DataFrames.
Prerequisites
- Anaconda or Miniconda installed
- OS Support
- Ubuntu 16.04/18.04/20.04 LTS
- CentOS 7
- GPU Support
- Pascal or Better
- Compute Capability >= 6.0
- CUDA Support
- 10.1.2
- 10.2
- 11.0
- Python Support
- 3.7
- 3.8
Updated 25 days ago
What's Next
Install via Conda |
Install via Docker |
Build From Source |
10 Minutes to BlazingSQL |
BlazingSQL Notebooks |