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Databases & Warehouses integrations for AI agents

Every operational database and analytics warehouse, one runtime. Agents read and write your data as a governed step in a flow, and stop for a human before the writes that carry risk, like a bulk delete or a change against a production table.

26 Integrations
326 Actions
5 Triggers
2 Real-time / polling

Airtable

Database

Use Airtable as a living operational database for your AI agents. 2 record triggers kick off workflows when data changes. 17 actions cover full CRUD across bases, tables, records, and comments.

2 triggers 17 actions

Amazon DynamoDB

Database

Read, write, query, and scan Amazon DynamoDB tables from automated flows. Agents persist workflow data, run PartiQL statements, and batch-load items with values returned as plain JSON.

10 actions

Azure Cosmos DB

Database

Connect AI agents to Azure Cosmos DB through the Core (SQL) API. Agents manage databases and containers and create, read, query, replace, upsert, and delete documents.

15 actions

Azure Table Storage

Database

Connect AI agents to Azure Table Storage, the NoSQL key/attribute store in Azure Storage. Agents manage tables and entities keyed by PartitionKey and RowKey with OData filter queries.

12 actions

Baserow

Database

Connect AI agents to Baserow, the open-source no-code database. Agents read and write rows and manage databases, tables, and fields on Baserow Cloud or a self-hosted instance.

15 actions

CrateDB

Database

Connect AI agents to CrateDB over its SQL-over-HTTP endpoint. Agents run parameterized SQL and high-throughput batched writes against distributed time-series and IoT data.

2 actions

Databricks

Database

Connect AI agents to the Databricks REST API. Agents run SQL on a warehouse, orchestrate jobs, manage clusters, browse Unity Catalog, and inspect DBFS and workspace paths.

24 actions

Elasticsearch

Database

Connect AI agents to Elasticsearch and Elastic Cloud. Agents index and search documents with full Query DSL, run bulk NDJSON operations, update or delete by query, and manage indices.

18 actions

FileMaker

Database

Connect AI agents to a FileMaker Server or FileMaker Cloud database through the Data API. Agents read, create, edit, find, and delete records, run scripts, and inspect layout metadata.

13 actions

Google BigQuery

Database

Connect AI agents to Google BigQuery. Agents run GoogleSQL with named parameters, stream rows into tables, read table data without query cost, and manage datasets and tables.

11 actions

Google Firestore

Database

Connect AI agents to Cloud Firestore. Agents create, read, update, delete, list, query, and aggregate documents with plain JSON in and plain JSON out.

9 actions

Grist

Database

Connect AI agents to Grist, the relational spreadsheet. Agents run record CRUD including upsert, manage tables and columns, discover documents, and run read-only SQL queries.

15 actions

Microsoft SQL Server

Database

Connect AI agents to Microsoft SQL Server and Azure SQL Database. Agents run parameterized T-SQL, do CRUD without SQL, inspect schemas, and bulk-load rows as steps in a flow.

9 actions

MongoDB

Database

Connect AI agents to MongoDB and MongoDB Atlas. Agents run the full document lifecycle, aggregation pipelines, collection and index management, and Atlas vector search.

22 actions

MySQL

Database

Connect AI agents to MySQL and MySQL-compatible servers such as MariaDB, PlanetScale, and Aurora. Agents run parameterized SQL, do CRUD without SQL, inspect schemas, and bulk-load rows.

9 actions

NocoDB

Database

Connect AI agents to NocoDB, the open-source no-code database. Agents read and write table records, manage linked records, provision tables, and inspect base and view metadata.

15 actions

Oracle Database

Database

Connect AI agents to Oracle Database in Thin mode (no Instant Client). Agents run SQL and PL/SQL, do CRUD without SQL, and inspect schemas as governed steps in a flow.

9 actions

PostgreSQL

Database

Connect AI agents to PostgreSQL. Agents run parameterized SQL, read and write rows without SQL, inspect schemas, and bulk-load records as governed steps in a flow.

9 actions

QuestDB

Database

Connect AI agents to QuestDB, the high-performance time-series SQL database. Agents run queries and DDL/DML over the REST API, export result sets as CSV, and validate connectivity.

3 actions

Quick Base

Database

Connect AI agents to Quick Base through the JSON REST API. Agents query, insert, update, and delete records, manage tables and fields, run reports, and download file attachments.

16 actions

Redis

Database

Connect AI agents to Redis. Agents cache values with TTL, maintain atomic counters and locks, work with hashes, lists, sets and sorted sets, publish messages, and read server stats.

26 actions

SeaTable

Database

Connect AI agents to a SeaTable base. Agents read, append, and update rows in bulk, run read-only SQL over base data, maintain row links, and discover table and column names.

13 actions

Snowflake

Database

Connect AI agents to Snowflake through the SQL API v2. Agents run parameterized SQL, load results into tables, poll long-running statements, and discover databases, schemas, and tables.

8 actions

Stackby

Database

Connect AI agents to Stackby, the spreadsheet-database. Agents create, read, update, and delete rows in a Stack table as governed steps in a flow.

5 actions

Supabase

Database

Real-time database operations and event triggers for Supabase. Agents react to record creation, updates, and deletion. Full CRUD with PostgREST filter support and dynamic table discovery.

3 triggers 4 actions

TimescaleDB

Database

Connect AI agents to TimescaleDB, the time-series database built on PostgreSQL. Agents run SQL, do CRUD without SQL, manage hypertables, run time_bucket rollups, and enforce chunk retention.

17 actions

Connect your databases & warehouses stack in minutes

$100 in credits. No card required. Every integration on this page is built and verified against the vendor's official API.