Drafting SQL from plain English
Turn a clearly defined data question and schema into a first-pass query for human review.
Independent tool overview
Chat Ur Data at a glance
Chat Ur Data is a custom GPT designed to connect conversational questions to databases, generate SQL, and help users explore data without starting every query from scratch.
Visit the official Chat Ur Data site ↗
- Product type
- Custom GPT for database querying and analysis
- Runs in
- ChatGPT
- Current access
- Direct GPT listing is active; sign-in is required
- Original integration
- External API and OAuth database connection
- Published database support
- PostgreSQL, MySQL, DuckDB, Snowflake, and more
- Separate tool fee
- None publicly listed
- ChatGPT Free
- $0 with usage limits
- ChatGPT Plus
- $20 per month
Overview
What Chat Ur Data is
Chat Ur Data is a custom GPT created for database work inside ChatGPT. Its original creator described it as connecting to databases through an external API and OAuth, while the product's published materials reference PostgreSQL, MySQL, DuckDB, Snowflake, and other systems. The direct GPT listing remains available, but users must sign in to inspect or run it.
Its best use is assisted analysis: describe a schema, ask a business question, review the proposed SQL, and run a carefully scoped query. It should not be treated as an autonomous database administrator. Generated queries can be incorrect, slow, destructive, or unsafe, and any connected action may send selected data to a third-party service.
Use cases
Who Chat Ur Data is best for
The strongest fit depends on the job you need the product to complete, not the size of its feature list.
Explaining unfamiliar schemas
Summarize table relationships, columns, joins, and likely data-model assumptions from sanitized definitions.
Debugging queries
Identify syntax issues, suspect joins, grouping mistakes, null handling, and dialect mismatches.
Exploratory analysis
Iterate on questions, aggregations, filters, and chart ideas while keeping an analyst in control.
Learning SQL
Ask for step-by-step explanations and compare alternate ways to answer the same database question.
Documenting data work
Translate approved queries and schema notes into readable descriptions for teammates.
Capabilities
Core Chat Ur Data features
Natural-language database questions
Users can describe the result they want conversationally instead of beginning with SQL syntax.
SQL generation
The GPT can draft queries based on supplied schema context and a named SQL dialect.
Connected database workflow
The original implementation used OAuth and an external API to connect the GPT to supported databases.
Schema-aware assistance
Published descriptions say it can learn a user's tables and use that context when composing queries.
Query explanation
Users can ask the assistant to explain joins, filters, aggregations, window functions, and assumptions.
Iterative refinement
Follow-up prompts can narrow a date range, add a segment, correct a field, or change the output shape.
Chart-oriented analysis
Its published listing includes making charts from query results, subject to the data and tools available in the current ChatGPT session.
File-based fallback
ChatGPT can analyze uploaded data files when plan limits and workspace policies permit, avoiding a live production connection for some tasks.
ChatGPT capabilities
Availability of browsing, file analysis, and other capabilities depends on the current GPT configuration and the user's ChatGPT plan.
Cross-database positioning
The tool has been presented as supporting common operational databases and warehouses rather than a single SQL engine.
Process
How the Chat Ur Data workflow works
Step 1
Remove sensitive information
Never paste passwords, connection strings, private keys, access tokens, or unnecessary personal data into a prompt.
Step 2
Choose the safest input
Prefer sanitized DDL, a data dictionary, and synthetic sample rows before connecting a live database.
Step 3
Name the SQL dialect
Specify PostgreSQL, MySQL, Snowflake, DuckDB, or the applicable engine and version.
Step 4
Define the question precisely
State the metric, grain, filters, date boundaries, timezone, and expected output columns.
Step 5
Request read-only SQL first
Ask for a SELECT statement and an explanation of every join, filter, and assumption.
Step 6
Inspect before execution
Review permissions, query plan, estimated scan, row multiplication, null behavior, and edge cases.
Step 7
Test outside production
Use a staging database, snapshot, transaction, row limit, or restricted read replica whenever possible.
Step 8
Validate the result
Compare totals with a trusted source, inspect samples, and have an owner approve consequential analysis or changes.
Cost
Chat Ur Data pricing and free plan
Chat Ur Data does not publish a separate subscription price. Access is governed by ChatGPT availability and limits. ChatGPT offers a Free plan and Plus at $20 per month; a paid plan does not guarantee that this third-party GPT or its external connection will remain available.
ChatGPT Free
$0
Signed-in users can use available GPTs subject to Free-tier model, message, file, and tool limits.
- No separate Chat Ur Data fee is publicly listed
- Usage and capability limits apply
- Availability of a specific GPT can change
ChatGPT Plus
$20/month
Higher ChatGPT limits and broader feature access than Free, subject to current OpenAI plan terms.
- Billed by OpenAI
- Does not include a guaranteed database service-level agreement
- External services may impose separate terms or limits
Pricing checked . Check current pricing at the source ↗
Assessment
Chat Ur Data strengths and limitations
Where it stands out
- Turns plain-language questions into a useful SQL starting point
- Keeps query explanation and revision in one conversation
- Can reduce the effort required to understand an unfamiliar schema
- Supports a broader database workflow than a generic writing assistant
- Useful for learning why a query works, not only receiving the final text
- Can help analysts document assumptions and hand off approved queries
- File or sanitized-schema workflows can avoid direct production access
- No separate public subscription is listed beyond ChatGPT access
What to consider
- The direct public page exposes the GPT title but not its full private instructions, action schema, or current connector configuration
- A public GPT can be changed, restricted, or removed by its builder without notice
- The original external API and OAuth workflow does not prove every previously advertised database remains operational today
- Any external action may send relevant prompt or database data to a third-party service governed by separate terms
- GPT builders cannot view individual ChatGPT conversations, but third-party action providers may receive data sent through their integrations
- Generated SQL can contain incorrect joins, invented columns, dialect errors, or faulty business assumptions
- A syntactically valid query can still be slow, expensive, insecure, or analytically wrong
- Never provide database passwords, full connection strings, private keys, or unrestricted production credentials
- Use a least-privilege read-only role and narrowly scoped datasets for any connection
- Do not execute generated DROP, TRUNCATE, GRANT, migration, bulk UPDATE, or bulk DELETE statements without expert review, backups, staging, and a tested rollback
- Uploading customer, employee, health, financial, or other regulated data may violate company policy or legal obligations
- Consumer ChatGPT conversations may be used to improve models depending on Data Controls; business offerings follow different defaults
- ChatGPT plan limits can interrupt longer schema, file, or data-analysis sessions
- GPT conversations do not automatically inherit saved memory, custom instructions, or previous chats
- Results require independent validation against trusted totals and source systems
- It is not a substitute for a database administrator, security review, data governance, or accountable analytical judgment
Compare
Chat Ur Data alternatives
The right alternative depends on the specific output, workflow, controls and budget your project requires.
Coding
AI2SQL
Choose AI2SQL for a purpose-built natural-language-to-SQL interface rather than a custom GPT workflow.
Explore AI2SQL →Coding
Database Builder
Choose Database Builder for another ChatGPT-based assistant focused specifically on PostgreSQL management.
Explore Database Builder →Business Operations
ChatGPT
Choose standard ChatGPT when sanitized schemas, uploaded files, and manually reviewed SQL are enough without a third-party database action.
Explore ChatGPT →Questions
Chat Ur Data FAQs
What is Chat Ur Data?
Chat Ur Data is a custom GPT for asking database questions in natural language, generating SQL, and analyzing results inside ChatGPT.
Is Chat Ur Data still active?
Its direct ChatGPT listing was available when reviewed on August 31, 2026, and required sign-in. The public page did not expose enough configuration detail to confirm every historical connector or action.
Which databases does Chat Ur Data support?
Published descriptions name PostgreSQL, MySQL, DuckDB, Snowflake, and additional databases. Confirm the current connector list after signing in because integrations can change.
Is Chat Ur Data free?
There is no separate public fee listed for Chat Ur Data. Existing GPTs can be available to signed-in Free users within ChatGPT limits; ChatGPT Plus costs $20 per month.
Can it connect directly to a production database?
The original implementation was described as using an external API and OAuth. Even if that connection remains available, use a restricted read-only account, limit accessible data, and test with non-production systems first.
Can I trust the SQL it generates?
No generated query should be trusted automatically. Check the schema, dialect, joins, filters, query plan, permissions, and results before using it for production or consequential decisions.
Is my database data private?
Data entered into ChatGPT is subject to OpenAI's plan and Data Controls, while data sent through a GPT action may also be processed by the third-party action provider. Review both sets of terms and avoid sensitive data unless your organization has approved the workflow.
Can the GPT creator read my chats?
OpenAI says GPT builders cannot view individual conversations with their GPTs. However, information sent to an external API or app can be received by that third party.
Should I let Chat Ur Data modify my database?
Avoid autonomous writes. Any schema change, permission change, migration, update, or deletion should go through normal review, backups, staging, transactions, monitoring, and rollback procedures.
Bottom line
Our Chat Ur Data verdict
Chat Ur Data is a useful conversational front end for drafting and explaining database queries, especially when the alternative is repeated manual translation from business questions to SQL. Its value depends on the current external connection and the quality of the schema context, however. Treat it as an assistant: minimize the data shared, use read-only access, inspect every query, and keep production changes under established engineering controls.
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