Source connector

Teradata connector

Teradata integration for databases, warehouses and BI tools

Teradata analytical database for enterprise workloads. Datrise captures Teradata entities such as tables, rows, schemas, indexes, primary indexes and query history, then lands normalized and typed models for warehouse reporting, attribution, and AI workflows.

The Teradata Vantage SQL (JDBC/ODBC/CLIv2 drivers) + Teradata Parallel Transporter (TPT) authenticates with username / password, JWT, incremental runs key on application-maintained watermark column, or SYSTEM_TIME period columns on an explicitly created ANSI Temporal (system-versioned) table.

Of the 6 objects, 5 sync as upserts keyed on the primary key and 1 as append-only streams, so each incremental run moves only what changed since the last watermark. Every object lands in its own table (for example `teradata_d_tables`) with a schema derived from the Teradata API rather than a flattened CSV, in any of the 43 supported destinations.

Datrise is in early access: pick a destination below to open the Teradata pipeline page, and join the waitlist to get the Teradata connector with guided onboarding.

Incremental syncSchema-aware mapping43 destinations available

What Teradata data Datrise extracts

Each object lands in its own typed table. Sync mode is derived from the object: history-style objects append, everything else upserts.

Object	Landing table	Sync mode
tables	teradata_d_tables	Upsert by primary key, incremental on updated-at
rows	teradata_d_rows	Upsert by primary key, incremental on updated-at
schemas	teradata_d_schemas	Upsert by primary key, incremental on updated-at
indexes	teradata_d_indexes	Upsert by primary key, incremental on updated-at
primary indexes	teradata_d_primary_indexes	Upsert by primary key, incremental on updated-at
query history	teradata_d_query_history	Append-only, incremental by timestamp

Teradata API: setup facts for the connector

Verified against the vendor documentation on 2026-09-02. Unknown values are left blank rather than guessed.

API	Teradata Vantage SQL (JDBC/ODBC/CLIv2 drivers) + Teradata Parallel Transporter (TPT)
Authentication	username / password, JWT — The default TD2 method needs only a database username/password; LDAP and Kerberos (KRB5) delegate to external directories, and newer OIDC methods (BEARER, BROWSER, CODE, JWT, ROPC) authenticate against an identity provider — all selected via the driver's `logmech` connection parameter.
Pagination	keyset — There is no vendor pagination token; rows are fetched via ordinary SQL `SELECT` with a driver-managed cursor, so incremental pulls are ordered and filtered by an application-chosen watermark column.
Rate limit	Not published
Incremental cursor	application-maintained watermark column, or SYSTEM_TIME period columns on an explicitly created ANSI Temporal (system-versioned) table — Teradata has no built-in binlog-style change feed; incremental extraction filters a watermark column you maintain yourself, or queries an ANSI Temporal table's system-time history if the table was created with that versioning enabled.
Webhooks	No
Bulk export	Yes — Teradata Parallel Transporter (TPT) EXPORT operator / standalone FastExport utility
Deletes detectable	No — not tracked by default on ordinary tables; only observable if the table was explicitly created as an ANSI Temporal (SYSTEM_TIME) table, or via custom triggers/audit tables built by the DBA

Official API reference

What bites when replicating Teradata

There is no built-in CDC feed: incremental extraction relies on either a watermark column you maintain yourself, or explicitly enabling ANSI Temporal (SYSTEM_TIME) versioning per table before any change history is captured at all.
Bulk export goes through Teradata Parallel Transporter's EXPORT operator or the standalone FastExport utility, not the JDBC/ODBC driver's row-by-row `SELECT` path, which is far slower for large tables.
The `logmech` connection parameter selects one of more than ten authentication methods (TD2, LDAP, KRB5, TDNEGO, BEARER, BROWSER, CODE, CRED, SECRET, ROPC, JWT); the OIDC methods additionally require the database user to have 'logon with null password' permission granted before they work.
FastLoad's error-table retry logic defaults to `error_query_count=21` attempts at an `error_query_interval` of 500ms, so a flaky connection during a bulk load can retry silently for over 10 seconds per batch before it finally fails.

Compare this against every other documented API

Popular destinations for Teradata

Choose a destination below to open the ready pipeline page.

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Airtable
Relational spreadsheet destination for ops and go-to-market teams.
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Amazon Athena
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Amazon DynamoDB
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Amazon QuickSight
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Amazon Redshift
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Amazon S3 Data Lake
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Apache Superset
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Azure Data Lake Storage
ADLS Gen2 object storage for analytics workloads.
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Azure Synapse
Microsoft analytics workspace with SQL pools.
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Teradata connector FAQ

What Teradata data does the connector extract?: 6 objects: tables, rows, schemas, indexes, primary indexes and query history. Each lands in its own table with types preserved; history-style objects (1: query history) load as append-only streams.
Is the Teradata integration incremental?: Yes. After the initial full load, every run reads only records changed since the last watermark (updated-at or event timestamp) and applies an upsert or an append depending on the object.
Where can I load Teradata data?: Into 43 destinations: relational databases, cloud warehouses, data lakes, spreadsheets and BI tools. Each Teradata → destination pair has its own page with the object-to-table mapping.

Related sources

Other sources in the same category, each with its own connector page.

Early access

Launch your Teradata pipeline with guided onboarding

Join the waitlist to get priority access for Teradata integrations with guided setup, schema-aware mapping, and production-grade incremental sync.