Coral — SQL Interface over APIs, Files, and Live Sources

Introduction

Coral is a Rust-based query engine that exposes APIs, local files, and live data sources through a standard SQL interface. Instead of writing custom code for each data source, you write SQL and Coral handles the translation. It is built with AI agents in mind, giving them a single familiar interface to query any data.

What Coral Does

• Lets you query REST APIs, CSV files, JSON, and databases using standard SQL
• Translates SQL queries into appropriate API calls or file reads automatically
• Provides a unified schema layer so different data sources look like SQL tables
• Supports joins across heterogeneous sources in a single query
• Ships as a single Rust binary with no runtime dependencies

Architecture Overview

Coral uses a SQL parser frontend that accepts standard SQL queries and a planning layer that maps table references to configured data source adapters. Each adapter knows how to translate SQL predicates and projections into native operations for its source — HTTP requests for APIs, file reads for local data, or pass-through queries for databases. The execution engine handles cross-source joins and aggregations in memory. Being written in Rust, Coral compiles to a single static binary with fast startup and low memory usage.

Self-Hosting & Configuration

• Build from source with Cargo or download pre-built binaries from releases
• Define data sources in a YAML configuration file with connection details and schema mappings
• Use the CLI for ad-hoc queries or run Coral as a server with an HTTP query endpoint
• Configure authentication for API sources using environment variables or the config file
• Extend with custom source adapters for proprietary data formats

Key Features

• Standard SQL syntax for querying any data source
• Cross-source joins between APIs, files, and databases in one query
• Single static binary with no runtime dependencies
• Built for AI agents that need structured data access
• Extensible adapter system for custom data sources

Comparison with Similar Tools

• Steampipe — SQL for cloud APIs with a Postgres wire protocol; Coral is a lighter single-binary tool
• Trino/Presto — distributed SQL engines for big data; Coral is a local-first tool for developer and agent use
• DuckDB — fast local analytics on files; Coral adds API and live source querying
• q — SQL on CSV/TSV files; Coral extends the concept to APIs and any structured source

FAQ

Q: What SQL dialect does Coral use? A: Coral supports standard SQL with extensions for configuring source-specific parameters.

Q: Can I use Coral as a library in my application? A: The primary interface is the CLI and HTTP server, but the Rust crate can be embedded in other applications.

Q: How does it handle API rate limits? A: Coral respects rate limit headers and can be configured with per-source request throttling.

Q: Is it suitable for large datasets? A: Coral processes data in memory, so it works best for moderate-sized results. For large-scale analytics, use dedicated engines like DuckDB or Trino.

Sources

• https://github.com/withcoral/coral