Copybooks parsed into BigQuery schemas. COBOL program logic becomes BigQuery SQL or PySpark on Dataproc. JCL job streams convert to Cloud Composer DAGs. VSAM and flat files land as BigQuery tables. Full lineage, validated parity.
Book a Live Demo →Mainframe batch jobs require MIPS capacity planning and z/OS maintenance. BigQuery runs SQL at warehouse scale with zero infrastructure. Pay per query, not per MIPS.
COBOL business rules with IF/ELSE, COMPUTE, and EVALUATE map cleanly to BigQuery SQL. Complex programs with nested PERFORM loops and table handling become PySpark on Dataproc, writing results back to BigQuery tables.
JCL defines job steps, dataset allocation, and execution order. Cloud Composer (managed Airflow) handles the same DAG orchestration with retry, alerting, and cross-service integration across GCP.
A COBOL copybook and batch program converted to BigQuery DDL and SQL. When logic requires Python, MigryX outputs PySpark on Dataproc instead.
COPY TXN-REC.
05 TXN-ID PIC X(12).
05 TXN-AMT PIC S9(7)V99 COMP-3.
05 TXN-TYPE PIC X(1).
88 CREDIT VALUE 'C'.
88 DEBIT VALUE 'D'.
05 ACCT-NO PIC X(10).
PROCEDURE DIVISION.
PERFORM UNTIL END-OF-FILE
READ TXN-FILE INTO TXN-REC
IF CREDIT
ADD TXN-AMT TO WS-TOTAL-CR
ELSE
ADD TXN-AMT TO WS-TOTAL-DB
END-IF
WRITE SUMMARY-REC
END-PERFORM.
-- Copybook → DDL
CREATE TABLE IF NOT EXISTS
`project.dataset.txn_summary` (
txn_id STRING,
txn_amt NUMERIC,
txn_type STRING,
acct_no STRING
);
-- Program → BigQuery SQL
SELECT
acct_no,
SUM(CASE WHEN txn_type = 'C'
THEN txn_amt ELSE 0 END)
AS total_credit,
SUM(CASE WHEN txn_type = 'D'
THEN txn_amt ELSE 0 END)
AS total_debit
FROM `project.dataset.txn_raw`
GROUP BY acct_no;PIC clauses become BigQuery types. 88-level conditions become CASE WHEN. COMP-3 becomes NUMERIC with preserved precision.
| COBOL / Mainframe | BigQuery / GCP Equivalent | Notes |
|---|---|---|
| COBOL program (simple) | BigQuery SQL script | Business rules as SQL logic |
| COBOL program (complex) | PySpark on Dataproc | Nested PERFORM, table handling |
| Copybook (PIC clauses) | BigQuery DDL | All PIC types mapped |
| COMP-3 packed decimal | NUMERIC | Precision and scale preserved |
| REDEFINES | STRUCT / JSON | Union record layouts handled |
| EVALUATE / IF-ELSE | CASE WHEN | Business rules preserved |
| 88-level conditions | CASE WHEN | Named conditions as filter logic |
| VSAM KSDS / ESDS | BigQuery table | GCS staging + LOAD DATA |
| Flat file (FB/VB) | BigQuery table | External table or LOAD DATA |
| DB2 SQL (EXEC SQL) | BigQuery SQL | DB2 dialect translated |
| JCL job stream | Cloud Composer DAG | Airflow orchestration |
Data Matching compares mainframe production output against BigQuery results — record by record, field by field. Packed decimal precision, date formats, and sign handling are all verified before cutover.
See how Data Matching works →Batch COBOL programs with copybooks and JCL converted to BigQuery SQL. Complex logic routed to PySpark on Dataproc. VSAM files staged to GCS and loaded. All outputs validated with Data Matching before mainframe decommission.
View case studies →Send us a copybook and sample program. Get parsed schema, BigQuery SQL, and a validation report.