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Teradata to Snowflake: what are the options?
There are two kinds of route. Convert the code, with SnowConvert AI (free from Snowflake), a partner tool such as Next Pathway or LeapLogic, or Novuz. Or keep the applications unchanged and translate their SQL at run time, with Snowflake AIM for Virtualization, the product Snowflake announced as Datometry for Snowflake. SnowConvert AI is the natural first step; the choice after it turns on BTEQ, proof and price. Here are the facts, from each vendor’s published material.
Side by side
How do the Teradata to Snowflake routes differ?
| SnowConvert AI | Snowflake AIM for Virtualization | Next Pathway | LeapLogic | Novuz | |
|---|---|---|---|---|---|
| Approach | Converts code to Snowflake; flags what it cannot convert for manual fixing | A gateway that translates Teradata SQL to Snowflake SQL at run time, so applications keep their code | Code and ETL translation, with planning (Crawler360) and testing (Tester) products | Pattern-based transformation engine with a rules engine | Fixed, versioned rules convert about 95% of objects; a resolver handles the rest, with engineer approval |
| Teradata coverage | SQL, stored procedures (to JavaScript procedures), BTEQ, FastLoad, MultiLoad, TPump and TPT (to Python) | Teradata 14.0 and later; Snowflake states at least 99.5% average syntax coverage for typical workloads | Teradata SQL, BTEQ scripts and stored procedures | Teradata including BTEQ, among many sources | Teradata SQL, BTEQ control flow, macros and procedures |
| Output | Snowflake SQL, Snowflake procedures and Python scripts | No converted code; the gateway stays in the path | Code for the target platform | An executable package with cloud-native orchestration | Native Snowflake code, plus a reconciliation report for every object |
| Equivalence evidence | See Snowflake documentation | A schema and query-log assessment is recommended to find workarounds | Tester validates data accuracy and functional equivalence; method not published | Schema, record, aggregate and cell-level validation | A reconciliation report for every object; typically above 95% on first pass |
| Where it runs | Desktop app and CLI | An RPM on Red Hat-compatible Linux VMs; two behind a load balancer in production | See Next Pathway documentation | See Impetus documentation | Inside your environment, as a Docker container or VM |
| Price | Free; professional services on request | Set in your Snowflake order form, plus Snowflake consumption; select customers | Not published | Not published; free trials listed | Fixed price per scope after a $3,000 assessment |
Re-verified monthly against each vendor’s published material. Last checked: 2026-11-03. Sources: Snowflake’s SnowConvert AI Teradata reference and FAQ, the AIM for Virtualization overview, Next Pathway’s Teradata migration page and Impetus’s LeapLogic material. An object counts as automated only if it needs no manual edit, and a one-line fix counts as manual.
When to choose
Which Teradata to Snowflake route should I choose?
- Run SnowConvert AI first. It is free, it covers BTEQ and the load utilities, and its output shows what is left.
- Choose Snowflake AIM for Virtualization if the priority is leaving Teradata fast without touching the applications, and you accept a gateway in the path and Snowflake-set pricing.
- Choose Next Pathway or LeapLogic if the program also covers sources such as Informatica, DataStage or SAS, or several targets.
- Choose Novuz if you need a fixed price before work starts and a reconciliation report for every object, including the objects SnowConvert AI converted.
- Choose an SI-led rewrite if the work is mostly redesign rather than conversion.
- Bottom line: convert with the free tool first, then decide on the remainder by what you must prove and when the price must be fixed.
Next question
Where to read next
What does a Teradata exit cost, and when should it start? The renewal page answers both.
Four pillars
What Novuz gives you that the other routes do not
Test any route against these four, ours included. Each one comes with a proof you can check yourself.
Deterministic
The same code in gives the same code out. About 95% of objects convert by fixed, versioned rules with no model calls. The rest go to the resolver, and an engineer approves every proposal.
Proof: Convert twice and diff the output. The diff is empty.
Proven
Every object ships with a reconciliation report. Schema, row counts and column-level values are compared against the original on the same inputs. Pass, fail or review, per object.
Proof: Reconciliation above 95% on first pass, typically.
Agentically primed
Agents can run Novuz through its APIs, and your agents can run the pipelines Novuz delivers through MCP. The conversion in between stays deterministic.
Proof: Conversion by rules, agents around it. No model in the conversion path.
Inside your walls
Runs as a container or VM in your cloud or your data center. Code, data, lineage and the resolver’s knowledge base stay with you. Works air-gapped.
Proof: No outbound connection required. Fixed price set before work starts.
Bottom line. Translation is the easy part. A comparison is worth making when the other route can show you the same output twice, a report for every object, agents around the conversion and code that never leaves your walls. If it cannot, that is what Novuz is for.
FAQ
Frequently asked questions
What tools migrate Teradata to Snowflake?
Snowflake’s free SnowConvert AI converts the code, including BTEQ and the load utilities. Snowflake AIM for Virtualization, announced as Datometry for Snowflake, translates SQL at run time instead. Partner tools include Next Pathway and LeapLogic. Novuz converts by fixed rules with a reconciliation report for every object.
Does SnowConvert AI convert BTEQ?
Yes. Snowflake’s documentation says BTEQ scripts, and FastLoad, MultiLoad, TPump and TPT scripts, are converted to Python scripts that call helper classes. Stored procedures become JavaScript procedures.
What is Datometry for Snowflake?
Snowflake announced Datometry for Snowflake in April 2026, and its documentation now describes the product as Snowflake AIM for Virtualization. It is a gateway that translates Teradata SQL to Snowflake at run time, so applications connect to it instead of Teradata. Snowflake lists it as available to select customers.
Should we virtualize or convert?
Virtualize when speed matters more than ending the dependency: the applications stay unchanged, and the gateway stays in the path. Convert when you want native Snowflake code and evidence per object. Some teams virtualize first and convert domain by domain.
Last reviewed:
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