Spice makes it easy for developers to create production-ready
AI-native data warehouses using Apache Arrow, DuckDB, and SQLite.
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Query structured and unstructed data using SQL across databases, data warehouses, and data lakes.
DocsSelf-hostable binary or Docker image, platform-agnostic, and Apache 2.0 licensed. Built on industry standard technologies including Apache DataFusion and Apache Arrow.
Materialize data and content in DuckDB, SQLite, and PostgreSQL; in-memory or on disk. Results caching included.
DocsLoad-balance across local models and OpenAI compatible endpoints with full observability, metrics, telemetry, query/task history, data flows, and tracing.
See how Spice has been deployed in production architectures.
Slow 15 sec queries across 100B+ rows.
Poor user experience with slow page loads.
Unnecessary Databricks workspace expense.
Unified SQL Interface for effortlessly materializing, accelerating, and querying data from any database, data warehouse, or data lake.
Accelerate and co-locate datasets with applications and frontends, to serve more concurrent queries and users with faster page loads and data updates
Faster, more responsive dashboards without massive compute costs.
Co-locate datasets in pipelines where the data is needed to minimize data-movement and improve query performance.
Federated SQL query across databases, data warehouses, and data lakes using Data Connectors.
Try materializing and querying Parquet files from S3, on your laptop, in under 60 seconds.
Announcing the release of Spice v0.17.3-beta. The v0.17.3-beta release further improves data accelerator robustness and adds a new `github` data connector that makes accelerating GitHub Issues, Pull Requests, Commits, and Blobs easy.
Announcing the release of Spice v0.17.2-beta 🏄 The v0.17.2-beta release focuses on improving data accelerator compatibility, stability, and performance. Expanded data type support for DuckDB, SQLite, and PostgreSQL data accelerators (and data connectors) enables significantly more data types to be accelerated. Error handling and logging has also been improved along with several bugs.
The v0.17.1-beta minor release focuses on enhancing stability, performance, and usability. The Flight interface now supports the `GetSchema` API and `s3`, `ftp`, `sftp`, `http`, `https`, and `databricks` data connectors have added support for a `client_timeout` parameter.
“We have been looking for a way to accelerate queries from our Databricks workspaces. Spice was the perfect solution, as it was super simple to setup and it was easy to define and query accelerated datasets without a lot of overhead.”
Chief Data Officer at Barracuda
