Skip to content
datarelix.ai docs

What Is Datarelix?

Datarelix is an AI-powered data client that transforms natural language questions into validated SQL/KQL queries and optional Python analysis.

Supported databases

  • PostgreSQL
  • MySQL
  • Azure SQL / Synapse
  • Databricks SQL
  • Kusto (Azure Data Explorer, KQL)
  • BigQuery
  • Amazon Athena
  • Elasticsearch (ES|QL, 8.11+)
  • Snowflake
  • Files & Object Storage (DuckDB — Parquet, CSV, JSON, Excel, Delta)

Key features

  • Natural language queries: ask questions like “What were our top customers last month?”
  • Validated execution: every generated query is parsed and validated before it runs.
  • Sandboxed Python analysis: charts, statistics, and complex transformations in an isolated runtime — no network access, strict resource limits.
  • Multi-dialect: one interface across your databases, warehouses, search clusters, and cloud files.
  • Sign-in: email and password to get started; SSO and per-user database identity (On-Behalf-Of) are available for workspaces — see Authentication.
  • API-first: every UI action is a REST endpoint. Programmatic keys are issued on request.
  • Fully managed: Datarelix runs the execution layer, the query services, and the sandbox — nothing to install or operate.

How it works

  1. Connect — add your database credentials (encrypted at rest).
  2. Ask — type a question in natural language.
  3. Plan — the model produces a structured plan, not direct tool calls.
  4. Execute — the execution layer validates and runs each step, against your database through an isolated query service, or in the sandbox for Python.
  5. Answer — you get an artifact-first result: tables, charts, and a short explanation, with full provenance.

Architecture at a glance

Datarelix is built around a strict execution boundary: the LLM never executes tools directly.

User question
    ↓
Execution layer
    ↓
The model produces a structured plan
    ↓
The execution layer validates and runs each step
    ├─→ Isolated query services (one per engine, read-only)
    └─→ Sandbox (isolated Python runtime)
    ↓
Artifact-first result

This separation means:

  • The LLM never has database credentials.
  • Every generated query is validated before execution — SQL dialects via sqlglot AST parsing; KQL and ES|QL via dedicated read-only validators.
  • Python runs in a sandbox with no network access and strict CPU/memory limits.
  • Every run is fully inspectable as a step-by-step trace.

Read more in Core Concepts.

Getting started

Ready to start? Head to the Quick Start Guide to set up Datarelix in minutes.

Privacy