Get the most out of your InterBase database with AI

Combining frontier AI models with InterBase, you can move faster and more safely while getting more value from your embedded or server deployment.

Chat with your InterBase database

SQLAI uses frontier AI models to turn natural-language questions into InterBase SQL. In a long-running conversation, follow-up questions can refine filters and calculations or explore a question in more detail without starting over. This ensures that you always get exactly what you want and helps you better understand what the generated query does.

SQLAI does not execute generated queries against InterBase today. Review the SQL in the conversation, then run it with isql, IBConsole or your application. Result rows are never added to the conversation automatically, but you can include a sample or summary in a follow-up if you want the model to consider it.

Try the Text-to-SQL demo to see a full conversation.

Import an InterBase schema

An InterBase schema can be pasted or uploaded as DDL, JSON or CSV, or described to the AI parser as documentation or another schema export. Direct connection is not available for InterBase. You can also select InterBase without attaching a schema. The public API engine name is interbase; see all supported databases and versions.

The imported schema and optional database rules give the AI context about your tables and relationships, helping it generate accurate, relevant SQL. Rules are a useful place to record the InterBase release, SQL dialect, page size, character set and generator conventions. SQLAI is built for large InterBase schemas: you don't have to trim your schema or paste it into every prompt, and the AI stays focused on the tables and columns that matter for your question as the schema grows. Learn more about how SQLAI keeps your database context in every chat.

See importing an InterBase schema in action.

Optimize InterBase queries

The SQL optimizer reviews slow InterBase queries and suggests rewrites or indexes intended to reduce execution time while preserving results. It can reason about index selectivity, composite indexes, join order, FIRST/SKIP, ROWS and the chosen plan. Firebird's optimizer and InterBase's optimizer share a lineage but have diverged, so verify suggestions against the actual InterBase release.

Optional deep analysis can compare a baseline and proposed rewrite using advanced evaluation matrices. This provides even more accurate optimization suggestions. The rewrite and its performance should still be verified against the production workload.

SET PLANONLY and the PLAN clause show how InterBase will execute a statement, and SET STATISTICS INDEX refreshes index statistics. See deep analysis in the SQL optimizer on a sample query.

Validate InterBase queries

The SQL validator performs an in-depth review of potential syntax and semantic issues, including invalid identifiers, type mismatches, ambiguous joins and InterBase-specific constructs. It explains findings and can suggest corrected SQL. Schema context can help with checking table names and relationships, but validation does not guarantee that a query matches the intended result.

Try the SQL validator on a query of your own.

Explain InterBase queries

The SQL explainer breaks down an existing query, including its joins, filters, aggregations, EXECUTE BLOCK logic and returned columns. Follow-up questions can focus on a particular clause, a generator or potential edge case.

Try the SQL explainer on a query you want to understand.

An imported InterBase database can be shared with teammates, who can use its schema and rules in their own chats. Only the owner can edit the database configuration. There is no live InterBase connection to share today, so teammates work from the shared schema rather than a live database.

Chat threads can be shared by invitation or link as read-only transcripts. Recipients can review the conversation, but only the owner can continue it. Query result rows are not saved in the thread.

Frequently asked questions

Do I need a live InterBase connection to use SQLAI?

No, and direct connections are not available for InterBase today. Import the schema by pasting or uploading DDL, JSON or CSV, or let AI parse a description of your schema. You can also select InterBase without attaching a schema.

Does SQLAI run queries against my database automatically?

No. SQLAI does not execute generated queries against InterBase today. Generated SQL is for you to review and run in isql or your application. Result rows are not added to a chat thread automatically.

Can SQLAI handle large InterBase schemas?

Yes. SQLAI is designed for large schemas with many tables and relationships. You can keep your whole schema imported, and responses stay focused on the tables and columns that matter as it grows. Learn more about how SQLAI keeps your database context in every chat.

Which InterBase versions are supported?

There is no version picker for InterBase, so the supported databases page lists the engine as covering all versions. Add the release, SQL dialect and page size to the database rules so generated SQL matches your deployment.

Is InterBase the same as Firebird?

No. Firebird began as a fork of InterBase, but the products have separate SQL dialects and optimizer behavior. Select interbase for InterBase and firebird for Firebird so the AI does not mix their syntax.

Review before production

AI-generated SQL queries can contain errors. Queries should be reviewed and their results and performance tested against a copy of the target InterBase database before production use. Check the plan, index statistics, page size and any embedded-deployment constraints.