NEW
Qlik to dbt
AI
Proof
Pricing
Book a demo
Scan your code free
NEW
Qlik to dbt
AI
Proof
Pricing
Book a demo
Scan your code free
Hard sources — not covered by free tools
Also parsed — certify what free tools miss
Runtimes
After migration
What's new
New sources, targets, and capabilities, newest first.
Two self-hosted images with the same engine. Each ships PostgreSQL 17, Python 3.12, and JDK 21. Only the UI port needs to be open.
See deployment options →Column lineage from Atlas can be written into dbt documentation, so the lineage stays with the models after go-live.
See Atlas →Talend jobs convert to Snowflake SQL and tasks, with the same row-level validation as other targets.
See Talend migration →When a block fails validation, MigryX AI reads the exception report and writes a plain-language reason next to the proposed fix.
See MigryX AI →The SAS parser now handles hash object lookups and user formats from PROC FORMAT without manual rewrites.
See SAS migration →A rebuilt discovery experience in Compass for scanning a legacy estate and building its inventory, lineage, and complexity view.
See Compass →Reusable mapplets are converted once and referenced from every mapping that uses them, instead of being copied inline.
See Informatica migration →Row-level comparisons now run inside Snowflake, so large tables are checked without moving data out.
See Snowflake →Convert to Polars or DuckDB with Apache Iceberg tables as the storage layer.
See Polars →Copybooks that use REDEFINES and OCCURS DEPENDING ON now map to typed target schemas.
See mainframe migration →Batch and iterative macros convert to reusable functions in PySpark or Python.
See Alteryx migration →The scan report now groups programs by team or owner, so each group can see its own share of the work.
See Compass →Parallel job stages convert to PySpark notebooks, with partitioning carried over where it matters.
See DataStage migration →Set per-column tolerances for rounding and timestamp formats, so expected differences are not reported as mismatches.
See how validation works →SQLForge now reads Denodo VQL views and semantic-layer definitions, alongside the SQL dialects it already handles.
See SQLForge →ODI mappings and knowledge modules convert to dbt models and macros.
See ODI migration →MigryX AI can run on a model hosted inside your network, for estates that cannot call an external service.
See MigryX AI →Set analysis expressions in Qlik load scripts and charts convert to filtered aggregates in SQL.
See Qlik migration →Validation results and lineage are bundled into a signed pack that auditors can review without access to MigryX.
See Atlas →Macros that build code at run time with CALL EXECUTE and %SYSFUNC are expanded and converted.
See SAS migration →Choose staging, intermediate, and mart folders for converted models, so output fits the layout your team already uses.
See dbt →Talend contexts convert to target configuration, with one file per environment.
See Talend migration →JCL steps and condition codes convert to orchestrated workflow tasks with the same run order.
See mainframe migration →PowerCenter mappings and workflows convert to PySpark and Databricks jobs.
See Informatica migration →Point the scanner at a folder of code and get an inventory and complexity report you can keep.
Scan your code →