COBOL to Snowflake

Why Snowflake

Mainframe data already feeds the warehouse

COBOL feeds become Snowflake-native

Many COBOL batch programs exist to extract, transform, and load data into downstream systems. When the destination is already Snowflake, the COBOL layer is just a pass-through. Move the logic into SQL procedures and eliminate the mainframe hop.

SQL for most logic, Snowpark for the rest

COBOL business rules with straightforward IF/ELSE and COMPUTE logic map cleanly to SQL CASE expressions. Complex programs with nested PERFORM loops and table handling become Snowpark Python DataFrames on Snowflake compute.

Snowflake Tasks replace JCL scheduling

JCL defines job dependencies, dataset allocation, and execution order. Snowflake Tasks handle the same scheduling with dependency chains, error handling, and Streams for change data capture.

Parser output

Copybook + COBOL logic to Snowflake SQL

A COBOL copybook and batch program converted to Snowflake DDL and a SQL procedure. When logic is too complex for SQL, MigryX outputs Snowpark Python instead.

COBOL Copybook + Program

       COPY CUST-REC.
       05 CUST-ID       PIC X(8).
       05 CUST-NAME     PIC X(30).
       05 ANNUAL-REV    PIC S9(9)V99 COMP-3.
       05 REGION-CD     PIC X(2).

       PROCEDURE DIVISION.
           PERFORM UNTIL END-OF-FILE
               READ CUST-FILE INTO CUST-REC
               EVALUATE TRUE
                   WHEN ANNUAL-REV > 1000000
                       MOVE 'ENTERPRISE' TO TIER
                   WHEN ANNUAL-REV > 100000
                       MOVE 'MID-MARKET' TO TIER
                   WHEN OTHER
                       MOVE 'SMB' TO TIER
               END-EVALUATE
               WRITE OUT-REC
           END-PERFORM.

→

MigryX
converts

Snowflake SQL

-- Copybook → DDL
CREATE TABLE IF NOT EXISTS cust_tiered (
    cust_id     VARCHAR(8),
    cust_name   VARCHAR(30),
    annual_rev  NUMBER(11,2),
    region_cd   VARCHAR(2),
    tier        VARCHAR(10)
);

-- Program → SQL procedure
CREATE OR REPLACE PROCEDURE classify_customers()
RETURNS STRING LANGUAGE SQL AS
$$
    INSERT INTO cust_tiered
    SELECT cust_id, cust_name, annual_rev,
           region_cd,
        CASE
            WHEN annual_rev > 1000000 THEN 'ENTERPRISE'
            WHEN annual_rev > 100000  THEN 'MID-MARKET'
            ELSE 'SMB'
        END AS tier
    FROM cust_raw;
    RETURN 'OK';
$$;

PIC clauses become Snowflake column types. EVALUATE becomes CASE. COMP-3 becomes NUMBER with preserved precision.

Coverage