Jailer

Jailer is a suite of specialized tools for AI-assisted SQL management, referential integrity preservation, and relational data browsing. It provides a system for generating referentially intact database subsets, allowing users to extract consistent slices of relational data while preserving foreign key constraints and dependencies.

The project features an AI-driven SQL assistant that uses natural language to generate, optimize, and refactor queries based on database schemas. It also includes a data migration tool that analyzes SQL patterns to reverse engineer models and map associations between database schemas.

The toolset covers relational data exploration through a visual browser that follows foreign key relationships. It further supports data subsetting through export and import transformations, recursive foreign key traversal, and the ability to manage null referential integrity.

Features

Relational Database Subsetting - Extracts a slice of database records while automatically including all related rows to maintain referential integrity.

Referential Integrity Management - Manages the export and import of database subsets while preserving foreign key constraints and dependencies.

SQL Assistants - Offers an AI-powered assistant for generating, optimizing, and refactoring SQL queries from natural language.

Natural Language to SQL - Translates natural language prompts into executable SQL queries for relational databases using schema metadata.

SQL Pattern Analysis - Analyzes SQL query patterns to automatically reverse engineer and map associations between database tables.

Recursive Dependency Collection - Walks relational graphs to identify and collect all dependent records required to maintain referential integrity.

Relation Navigators - Provides a UI for navigating between related database records using foreign key references.

Relational State Restoration - Loads an extracted data slice into a target database to recreate a specific relational state.

Export Criteria Filtering - Filters exported rows using association restrictions and metadata predicates to prevent data bloat.

Traversal Depth Limits - Limits the depth of relational traversal during data extraction to prevent excessive data bloat.

Query-Based Schema Reverse Engineering - Analyzes SQL statements and defines table associations based on observed query patterns.

SQL Optimization Assistants - Analyzes and refactors SQL statements using artificial intelligence to improve performance and logic.

Extraction Model Migrations - Updates data extraction models to match current database schemas by analyzing changes and resolving associations.

Query-Pattern Association Inference - Infers relational associations between tables by analyzing the join patterns found in executed SQL statements.

Referential Nullification Strategies - Sets foreign key columns to null when an associated parent row is missing from the subset.

SQL Query Execution - Provides an interface for running SQL statements and retrieving structured results with integrated developer tools.

SQL Query Optimizations - Analyzes SQL syntax and metadata to refactor and normalize queries for better execution efficiency.

Column-Level Export Transformations - Applies SQL expressions to table columns to modify values before writing them to an export file.

Import-Time Expression Evaluation - Executes SQL expressions during the import phase to transform values or generate new primary keys.

Import-Export Value Transformations - Evaluates SQL expressions during export and import phases to modify values or inject literal commands.

Database GUIs - Database subsetting and relational data browsing tool.

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Features

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