Connect your data to Spice

Spice connects to 30+ databases, warehouses, lakes, APIs, and streams. Federate SQL across your data stack, accelerate working sets, and build fast, intelligent applications.

Connect to 30+ data sources

Spice integrates with the systems modern teams rely on - databases, warehouses, data lakes, streaming systems, APIs, and search indexes. Our data connectors enable you to query data where it already lives using standard SQL, accelerate working sets locally, and integrate operational and analytical datasets into one unified runtime.

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DynamoDB

Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability. This connector enables using DynamoDB tables as data sources for federated SQL queries in Spice.

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Kafka

Kafka is an open-source distributed event streaming platform used for high-performance data pipelines, streaming analytics, and data integration. The Kafka Data Connector enables direct acceleration of data from Apache Kafka topics.

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Debezium

Debezium is an open-source platform that enables Change Data Capture (CDC) for efficient real-time updates of locally accelerated datasets. Spice supports connecting to a Kafka topic managed by Debezium to keep datasets up-to-date with source data.

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Clickhouse

ClickHouse is a fast, open-source columnar database management system designed for online analytical processing (OLAP) and real-time analytics. This connector enables federated SQL queries from a ClickHouse server.

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Microsoft SharePoint

SharePoint is web-based collaboration and document management platform. The SharePoint Data Connector enables federated SQL queries on documents stored in SharePoint.

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Oracle

Oracle offers a comprehensive and fully integrated cloud platform service. The Oracle Data Connector enables SQL queries on data stored in Oracle databases, including on-premises instances, Oracle Cloud User-Managed Databases, and Oracle Cloud Autonomous Databases (ADB).

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Apache Iceberg

Apache Iceberg is a high-performance format for huge analytic tables. The Iceberg Data Connector helps query Apache Iceberg tables using federated SQL.

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Apache Spark

Apache Spark is a multi-language engine for executing data engineering, data science, and machine learning. Use the connector for federated SQL queries against a Spark Cluster using Spark Connect

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ODBC

ODBC (Open Database Connectivity) is a standard API that allows applications to connect to and interact with various database management systems using a common interface. Connect to any ODBC database for federated/accelerated SQL queries with the Spice ODBC Connector.

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Microsoft SQL Server

Microsoft SQL Server (MSSQL) is a proprietary relational database management system (RDBMS). The Microsoft SQL Server Data Connector enables federated/accelerated SQL queries on data stored in MSSQL databases.

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FlightSQL

FlightSQL is an open-source protocol built on Apache Arrow Flight for high-performance, columnar data transfer between SQL databases and clients. Use the connector for federated SQL queries across any Flight SQL compatible server.

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GraphQL

GraphQL is an open‑source query language for APIs and a server‑side runtime. The GraphQL Data Connector enables federated SQL queries on any GraphQL endpoint

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Delta Lake

An open-source storage layer that improves the reliability and performance of data lakes by bringing database-like features such as ACID transactions and schema enforcement. The Delta Lake data connector enables SQL queries from Delta Lake tables.

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Dremio

Dremio is a data lake engine that enables high-performance SQL queries directly on data lake storage. This connector enables using Dremio as a data source for federated SQL queries.

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DuckDB

DuckDB is an in-process SQL OLAP (Online Analytical Processing) database management system designed for analytical query workloads. This connector supports DuckDB persistent databases as a data source for federated SQL queries.

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MySQL

MySQL is an open-source relational database management system that uses structured query language (SQL) for managing and manipulating databases. The MySQL Data Connector enables federated/accelerated SQL queries on data stored in MySQL databases.

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PostgreSQL

PostgreSQL is an advanced open-source relational database management system known for its robustness, extensibility, and support for SQL compliance. The PostgreSQL Server Data Connector enables federated/accelerated SQL queries on data stored in PostgreSQL databases.

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GitHub

GitHub is a developer platform that allows developers to create, store, manage, and share their code. The GitHub Data Connector enables federated SQL queries on various GitHub resources such as files, issues, pull requests, and commits.

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MongoDB

MongoDB is an open-source NoSQL database that stores data in flexible, JSON-like documents, allowing for dynamic schemas and easy scalability. The MongoDB Data Connector enables federated/accelerated SQL queries on data stored in MongoDB databases.

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Snowflake

Snowflake is a cloud data platform that allows for data analysis and simultaneous access of data sets with minimal latency. The Snowflake Data Connector enables federated SQL queries across datasets in the Snowflake Cloud Data Warehouse.

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Databricks

Databricks is a cloud-based platform for data analytics and artificial intelligence. Use the connector for federated SQL queries against Databricks using Spark Connect, directly from Delta Lake tables, or using the SQL Statement Execution API.

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ABFS

The Azure Blob Filesystem driver (ABFS) is a dedicated Azure Storage driver for Hadoop. The Azure BlobFS (ABFS) Data Connector enables federated SQL queries on files stored in Azure Blob-compatible endpoints.

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Deployed in production

Teams trust Spice to bring inference closer to their data, enabling low-latency, enterprise-grade AI across industries.

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"Partnering with Spice AI has transformed how NRC Health delivers AI-driven insights. By unifying siloed data across systems, we accelerated AI feature development, reducing time-to-market from months to weeks - and sometimes days. With predictable costs and faster innovation, Spice isn't just solving some of our data and AI challenges - it’s helping us redefine personalized healthcare.”

Tim Ottersburg

VP of Technology, NRC Health

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“Spice AI grounds AI in our actual data, using SQL queries across all our data. This brings accuracy to probabilistic AI systems, which are very prone to hallucinations.”

Rachel Wong

CTO, Basis Set

Integrations across all of your data sources

Accelerate your data and AI stack with a library of 30+ prebuilt connectors for the most common databases, warehouses, and file stores— - from Databricks and S3 to MySQL and PostgreSQL. Govern AI sandboxes with the same policies as your production data environments.

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See Spice in action

Get a guided walkthrough of how development teams use Spice to query, accelerate, and integrate AI for mission-critical workloads.

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