DB2
Generate, optimize, validate, format, and explain queries for DB2 with AI.
- Import schema
Go to DB2
Database + AI
Master Databases and Data With AI
Browse 28 supported databases and see how you can use AI to get the data you need, optimize SQL performance, get database indexes, validate SQL, understand SQL and much more. Connect directly to 6 engines or use schema context.
AI Databases
Explore supported databases
Search relational, analytics, NoSQL, graph, and query-layer engines.
- Visible
- 28
- Live connect
- 6
- Schema only
- 22
Searches database names, engine categories, and workflow summaries.
Showing 28 databases for browse every supported engine.
Relational databases
Classic SQL engines and operational databases used for transactional workloads and application backends.
MariaDB
Generate, optimize, validate, format, and explain queries for MariaDB with AI.
- Connect live
- Import schema
Go to MariaDBMicrosoft Access
Generate, optimize, validate, format, and explain queries for Microsoft Access with AI.
- Import schema
Go to Microsoft AccessMySQL
Generate, optimize, validate, format, and explain SQL for your MySQL database with AI.
- Connect live
- Import schema
Go to MySQLOracle PL/SQL
Generate, optimize, validate, format, and explain queries for Oracle PL/SQL with AI.
- Connect live
- Import schema
Go to Oracle PL/SQLPostgreSQL
Generate, optimize, validate, format, and explain queries for PostgreSQL with AI.
- Connect live
- Import schema
Go to PostgreSQLSQL (native)
Generate, optimize, validate, format, and explain queries for SQL (native) with AI.
- Import schema
Go to SQL (native)SQL Server (MS)
Generate, optimize, validate, format, and explain queries for SQL Server (MS) with AI.
- Connect live
- Import schema
Go to SQL Server (MS)SQLite
Generate, optimize, validate, format, and explain queries for SQLite with AI.
- Import schema
Go to SQLiteSybase
Generate, optimize, validate, format, and explain queries for Sybase with AI.
- Import schema
Go to Sybase
Analytics and warehouse engines
Columnar, warehouse, and large-scale analytical engines designed for reporting and performance-heavy query workloads.
Apache Hive
Generate, optimize, validate, format, and explain queries for Apache Hive with AI.
- Import schema
Go to Apache HiveBigQuery
Generate, optimize, validate, format, and explain queries for BigQuery with AI.
- Import schema
Go to BigQueryClickHouse
Generate, optimize, validate, format, and explain queries for ClickHouse with AI.
- Import schema
Go to ClickHousePresto
Generate, optimize, validate, format, and explain queries for Presto with AI.
- Import schema
Go to PrestoRedshift
Generate, optimize, validate, format, and explain queries for Redshift with AI.
- Import schema
Go to RedshiftSAP Hana
Generate, optimize, validate, format, and explain queries for SAP Hana with AI.
- Import schema
Go to SAP HanaSnowflake
Generate, optimize, validate, format, and explain queries for Snowflake with AI.
- Import schema
Go to SnowflakeSplunk
Generate, optimize, validate, format, and explain queries for Splunk with AI.
- Import schema
Go to SplunkTrino SQL (AWS Athena)
Generate, optimize, validate, format, and explain queries for Trino SQL (AWS Athena) with AI.
- Import schema
Go to Trino SQL (AWS Athena)Vertica
Generate, optimize, validate, format, and explain queries for Vertica with AI.
- Import schema
Go to Vertica
NoSQL and semi-structured databases
Document, key-value, and wide-column systems where AI still benefits from schema context and query guidance.
Cassandra
Generate, optimize, validate, format, and explain queries for Cassandra with AI.
- Import schema
Go to CassandraDynamoDB
Generate, optimize, validate, format, and explain queries for DynamoDB with AI.
- Import schema
Go to DynamoDBMongoDB
Generate, optimize, validate, format, and explain queries for MongoDB with AI.
- Connect live
- Import schema
Go to MongoDB
Graph and multi-model databases
Engines focused on connected data, graph traversals, and relationship-heavy query patterns.
Query languages and federated layers
Query abstractions, APIs, and federated engines that sit between applications and underlying data sources.
GraphQL
Generate, optimize, validate, format, and explain queries for GraphQL with AI.
- Import schema
Go to GraphQLPartiQL
Generate, optimize, validate, format, and explain queries for PartiQL with AI.
- Import schema
Go to PartiQLSalesforce SOQL/SOSL
Generate, optimize, validate, format, and explain queries for Salesforce SOQL/SOSL with AI.
- Import schema
Go to Salesforce SOQL/SOSL
SQL and NoSQL database support for AI query workflows
SQLAI.ai supports popular relational and non-relational engines so you can generate SQL from natural language, validate syntax, format queries, optimize performance, and explain query logic in one workflow.
Popular supported databases include MySQL, PostgreSQL, SQL Server (MS), Oracle PL/SQL, BigQuery, SQL (native), MariaDB, SQLite, Snowflake, DB2. Use search above to find a specific engine and open its dedicated page.
What you can do with supported databases
- Generate SQL queries from text prompts with schema-aware context.
- Optimize SQL for speed with rewrite suggestions and index-aware improvements.
- Validate SQL syntax and fix common query errors before execution.
- Format SQL for readability and explain complex SQL in plain language.
Use SQLAI tools across database engines
Each supported database can be used with SQLAI.ai tools for generation, optimization, validation, formatting, and explanation.