Dataherald vs Tablix
Dataherald
github.comTablix
tablix.aiSide by side
| Figure | Dataherald | Tablix |
|---|---|---|
| Price from | — | — |
| Free plan | — | — |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 0 | 0 |
| Spec score · AI Database Assistants | 7.7 (#11) | 6.9 (#19) |
| Database support | The quick start lists PostgreSQL, BigQuery, Databricks, and Snowflake as currently supported warehouse connections. | The same server and dashboard can connect to SQLite, PostgreSQL, MySQL, and SQL Server. |
| Deployment | The quick start describes self-hosting the engine with Docker, with Mongo running in a separate container for application data. | Docker Compose starts the server, dashboard, MCP endpoint, product state, and a sample SQLite database. |
| Intended users | The documentation is intended for developers building natural-language interfaces from structured data in their own projects and contributors to the engine. | The site identifies coding agents, data and platform teams, AI engineers, DevOps and SRE teams, and teams onboarding legacy schemas as use cases. |
| License | The GitHub repository identifies the project as licensed under Apache-2.0. | The site describes Tablix as MIT licensed. |
| Product | Dataherald is a natural language-to-SQL engine that exposes an API for asking questions about relational data in plain English. | Tablix is a self-hosted .NET server and React dashboard for asking natural-language questions of databases. |
| What it does | Dataherald is a natural language-to-SQL engine that lets users ask questions in plain English about structured or relational data through an API. | Tablix connects databases to people and AI agents so they can ask natural-language questions and get answers backed by executed queries. |
In their own words
Dataherald
Dataherald is an open-source natural language-to-SQL engine that exposes an API for asking questions about relational data in plain English. Its stated uses include helping business users query warehouses, embedding data Q&A in SaaS products, and creating ChatGPT plug-ins for proprietary data. The project targets developers building natural-language interfaces or contributing to the engine. Self-hosting uses Docker, with MongoDB in a separate container for application data. Listed warehouse connections are PostgreSQL, BigQuery, Databricks, and Snowflake. Included SQL-generation approaches are LangChain SQL Agent, LangChain SQL Chain, LlamaIndex SQL Generator, and Dataherald SQL Agent. A context store can include business and database details, validated question-and-SQL examples, and table information; active learning from usage is also described. An evaluator assigns confidence scores to generated SQL. The modular architecture allows implementations to be changed through .env configuration. Startup requires an OpenAI API key, organization ID, and encryption key. Connection data is encrypted before Mongo storage. The repository uses Apache-2.0 licensing.
Tablix
Tablix is an open-source, self-hosted.NET server and React dashboard for asking natural-language questions of databases. It connects to SQLite, PostgreSQL, MySQL, and SQL Server and returns answers with executed SQL, rows, row counts, and evidence. It scans tables, keys, indexes, and relationships, then creates editable database and table context. Workflows are available in the dashboard, through MCP for agents, and through REST for applications and automation. The dashboard includes setup, schema browsing, context editing, query execution, chat, and CSV or JSON exports. Tablix can use Ollama, OpenAI, OpenAI-compatible endpoints, or Gemini; database chat and MCP require tool-calling support. Statement types can be allowed per database, calls are scoped to the selected connection, and multi-statement SQL is rejected. The project states there is no cloud dependency or telemetry, with outbound calls limited to the configured model provider. Docker Compose starts the server, dashboard, MCP endpoint, state, and sample SQLite database.