# Teradata integrations: queries and sessions

> Submit a query, create a session and create or update a target system in Teradata.

**Canonical page:** https://tray.ai/connectors/teradata-integrations/
**Categories:** Data and analytics
**Connects through:** HTTP Connector

## Overview

Teradata is a data warehouse and analytics database, and its Query Service lets applications run SQL and browse database objects over HTTP without a driver. Tray.ai connects to Teradata through the HTTP Connector, so your workflows can call the Teradata API alongside the rest of your stack.

## Use cases

### Queries

Read, create, and delete queries in Teradata from any Tray.ai workflow. The Teradata API covers calls such as submit a query and list queries.

- Submit a query
- List queries
- Get a query

### Sessions

Read and create sessions in Teradata from any Tray.ai workflow. The Teradata API covers calls such as list sessions and create a session.

- List sessions
- Create a session
- Get a session

### Systems

Read, create, and delete systems in Teradata from any Tray.ai workflow. The Teradata API covers calls such as list target systems and get a target system.

- List target systems
- Get a target system
- Create or update a target system

### Databases

Read databases in Teradata from any Tray.ai workflow. The Teradata API covers calls such as list databases and get a database.

- List databases
- Get a database
- List tables

## Challenges Tray.ai solves

### Keeping Teradata credentials out of logs

A raw API call usually means pasting a key or token into the request, where it ends up in step inputs, logs, and screenshots.

**How Tray.ai helps:** Store Teradata credentials once as a Tray.ai authentication and reference them from the HTTP Connector. Tray.ai masks authentication values in logs, so the secret never shows up in a step's input or output.

### Going from the Teradata API docs to a working call

Translating an example request from API docs into a workflow step means copying the method, URL, headers, and body by hand.

**How Tray.ai helps:** Paste a cURL example from the Teradata API docs into the HTTP Connector and Tray.ai fills in the method, URL, headers, and body for you.

### Handling files and non-JSON responses

Not every API answers in JSON. Some return XML, files, or binary data, or expect a multipart upload.

**How Tray.ai helps:** The HTTP Connector parses JSON and XML responses, returns files you can pass to the next step, and sends multipart form data for uploads.

## Frequently asked questions

### Does Tray.ai connect to Teradata?

Yes. Tray.ai connects to Teradata through the HTTP Connector, which calls the Teradata API directly. Any call the Teradata API documents can run as a step in a Tray.ai workflow.

### How does Tray.ai authenticate with Teradata?

The Teradata API uses basic authentication and a bearer token. You save it once as a Tray.ai authentication, and the HTTP Connector adds it to every request.

### Can I get a dedicated Teradata connector?

Teradata runs through the HTTP Connector rather than a dedicated connector. If your team wants one, the Tray.ai connector SDK can build a dedicated Teradata connector from the Teradata API.

## Learn more

- Intelligent Integration: https://tray.ai/platform/intelligent-ipaas/
- Merlin Agent Builder: https://tray.ai/platform/merlin-agent-builder/
- Agent Gateway for MCP: https://tray.ai/platform/agent-gateway/
- Book a demo: https://tray.ai/contact/