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GitHub - spiceai/spiceai: A unified SQL query interface and portable runtime to locally materialize, accelerate, and query data tables sourced from any database, data warehouse, or data lake.

Mar 28, 2024 - github.com
Spice.ai is an open-source software that provides developers with a unified SQL query interface for data tables sourced from any database, data warehouse, or data lake. It simplifies the use of data and machine learning in software, making it easy to build data-driven applications. The Spice runtime is written in Rust and uses technologies like Apache DataFusion, Apache Arrow, Apache Arrow Flight, and DuckDB. It allows for simple and fast querying of data across multiple data sources and can co-locate a managed working set of data with your application or machine learning model for high-performance, low-latency queries.

The software is currently in the alpha stage of development and is not intended for production use until its 1.0-stable release. It supports data connectors for upstream datasets and data stores for local materialization/acceleration. Developers can use Spice.ai to build both data and AI-driven applications by co-locating data and ML models with applications. It also provides a quickstart guide for macOS, Linux, and WSL, and a roadmap for upcoming features. The team encourages feedback, suggestions, and contributions from the community.

Key takeaways:

  • Spice.ai is an open-source software that provides developers with a unified SQL query interface to locally materialize, accelerate, and query data tables sourced from any database, data warehouse, or data lake.
  • It is designed to make it easy to build data-driven and data-intensive applications by streamlining the use of data and machine learning in software.
  • Spice.ai supports a variety of data connectors and data stores, and it enables developers to build both data and AI-driven applications by co-locating data and ML models with applications.
  • It is currently under active alpha stage development and is not intended to be used in production until its 1.0-stable release.
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