Teradata migration
Teradata migration: convert the workload, not just the tables.
Teradata estates grow decades of BTEQ scripts, macros and reports. The migration is an inventory of that logic, converted and tested against the source.
The short answer
A Teradata migration moves data and workloads to a platform such as Snowflake or Databricks, or to a Postgres-based MPP database. The data copy is the smaller part. The larger part is converting BTEQ scripts, macros, stored procedures and Teradata SQL, then proving every report matches. Ace8 uses conversion tools and engineer review.
Targets
Should you move Teradata to Snowflake, Databricks or something else?
Choose from the workload, the team's skills and the three-year cost. We are not tied to one platform. The wider architecture question is on data warehouse modernization.
| Target | Good fit when | Watch for |
|---|---|---|
| Snowflake | SQL-centric analytics, many business consumers, variable demand | Cost control on heavy always-on jobs |
| Databricks | Warehouse plus data science, streaming and open table formats | SQL teams need time to adapt to the platform |
| Postgres-based MPP | Cost-sensitive, open-source or on-premises needs | Scale limits and fewer managed features |
The core of the project
What has to be converted from Teradata?
| Teradata feature | Typical replacement | What needs care |
|---|---|---|
| BTEQ scripts | Orchestrated SQL tasks (Airflow, dbt, platform tasks) | Embedded control flow and error handling |
| Macros and stored procedures | Views, procedures or dbt models | Logic hidden in nested macros |
| Teradata SQL dialect, such as QUALIFY and date arithmetic | Target dialect equivalents | Rounding, date and null handling differences |
| Primary index and partitioning | Clustering keys, micro-partitions or distribution settings | Teradata tuning does not translate directly |
| Fastload, MultiLoad and TPT jobs | Cloud stage and bulk load, or an ELT tool | Restart and error-table behavior |
| Set tables and duplicate handling | Explicit deduplication | Teradata set semantics are implicit |
| Workload management rules | Warehouse sizing or queues | Priorities rebuilt from usage |
Tooling
What tools help with the conversion?
Snowflake provides SnowConvert for converting Teradata SQL and scripts. Databricks provides migration tooling for converting SQL from legacy warehouses. Third-party translators exist too. Tools differ in coverage by version, so we run them on a sample of your real code first and measure what percentage converts cleanly.
Tool output is a starting point. A converted query that runs is not proof it returns the same numbers. That is why the validation step exists.
Method
How does a Teradata migration proceed?
- 1
Inventory and usage analysis
Use query logs to find what is queried, by whom, and what is dead. Retire what nobody reads.
- 2
Wave plan
Group workloads by data subject area and dependency. Migrate one wave at a time.
- 3
Convert and fix
Run conversion tools, then fix flagged code by hand.
- 4
Move the data
Export history, load to the target, then sync changes during the wave.
- 5
Compare and run in parallel
Run old and new side by side. Diff outputs on the reports people use.
- 6
Decommission
Switch consumers, then retire Teradata when the final wave has held through a full reporting cycle.
Cost
What sets the cost of a Teradata migration?
We show these factors in the assessment and publish no savings figure before we have your numbers.
- Lines of BTEQ, macros and procedural code to convert.
- Number of distinct reports and downstream consumers.
- Data volume and available network bandwidth.
- Length of the dual-running period.
- Target platform run cost, which can rise with careless design.
Analyze usage, convert BTEQ and SQL with a tool such as SnowConvert, move history to cloud storage and load it, sync changes, run both in parallel, then cut over by wave.
Snowflake suits SQL-centric analytics with many consumers. Databricks suits teams combining warehouse, data science and streaming. Choose from your workload and skills.
Months for most estates, driven by code volume and number of consumers. A wave plan shows results earlier than a single cutover.
Tools convert a large share of syntax. Control flow, error handling and unusual features need manual work and testing.
No. Usage analysis often shows unused tables and jobs that can be retired instead of migrated.
For smaller or cost-sensitive warehouses, a Postgres-based MPP can work. Large scale workloads usually go to a cloud platform.
Know the cost before anything moves.
A fixed-price assessment gives you the inventory, the risk score and a phased plan. Scope and cost are fixed before the migration starts.
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