Raw Query is a chat-based database tool that uses AI to let people work with data in plain English. It is built for tasks such as asking for recent records, adding new data, updating existing entries, and exporting results as CSV.
The service describes itself as a data assistant and says it can query data, insert new data with confirmation before the change is made, and update data. It also gives examples of finding the email addresses of recent clients and handling situations where there is no form for a new entry. In its FAQ, Raw Query says that natural language means plain English and that users can ask it in the chat instead of writing SQL or waiting for a developer. It also says it can save time for people building dashboards and internal tools, and mentions business intelligence users as another audience.
Raw Query connects to a database by pasting a connection string, and it says setup takes about 10 seconds. The FAQ states that it currently supports Postgres, MySQL, and MariaDB, with insert and update available only for Postgres and select-only access for the other two databases. It also says the service works on mobile devices. Security-related statements on the page say that it does not store actual data and that connection strings are stored as hashed values.
Pricing shown on the site includes a Free plan at $0 per month with 300 successful queries, 1 seat, and 2 databases; a Starter plan at $39 per month with 1,500 successful queries, 5 seats, unlimited databases, and priority support; a Pro plan at $79 per month with 5,000 successful queries, 10 seats, unlimited databases, and priority support; and a Team plan at $149 per month with 20,000 successful queries, unlimited seats, unlimited databases, priority support, and role access per database.
Raw Query is an AI project. It enables users to access, query, and update database information without writing SQL or using complex tools. It is built as a B2B product for business analysts. Raw Query is available on the web.
Raw Query first shipped in 2024. Among its 8 catalogued features are natural language queries, data export, and insert data.
Summary written by a language model from the project’s public pages.
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