Move data, schema, and routines from Google BigQuery to Oracle using export, transform, and load steps.
Teams consolidate analytics and OLTP workloads, cut cloud costs, or join Oracle-only systems. Oracle offers mature ACID transactions, partitioning, and on-prem control.
Three practical options: 1) CSV/Parquet export + SQL*Loader, 2) BigQuery → Cloud Storage → Oracle External Tables, 3) Oracle Database Gateway for BigQuery with INSERT SELECT over DB Link.
Use bq extract with compressed Parquet to Cloud Storage.Parquet preserves data types and is splittable for parallel load.
bq extract --destination_format=PARQUET \
--compression=SNAPPY \
ecommerce.Orders gs://bq_oracle_stage/Orders_*.parquet
Map BigQuery types to Oracle equivalents before load. Example: STRING → VARCHAR2, INT64 → NUMBER, TIMESTAMP → TIMESTAMP(6).
CREATE TABLE Orders (
id NUMBER PRIMARY KEY,
customer_id NUMBER REFERENCES Customers(id),
order_date DATE,
total_amount NUMBER(14,2)
);
SQL*Loader and external tables share a control file syntax.External tables avoid staging into redo logs, saving space.
CREATE TABLE ext_orders
ORGANIZATION EXTERNAL (
TYPE ORACLE_LOADER
DEFAULT DIRECTORY gcs_stage
ACCESS PARAMETERS (
records delimited by newline
preprocessor gcs_parquet
)
LOCATION ('Orders_001.parquet', 'Orders_002.parquet')
)
REJECT LIMIT UNLIMITED;
Use INSERT APPEND for new tables or MERGE for incremental syncs.
INSERT /*+ APPEND */ INTO Orders SELECT * FROM ext_orders;
Yes.Configure Oracle Database Gateway for BigQuery, create a DB Link, then pull data.
INSERT /*+ PARALLEL(8) */ INTO Orders
SELECT * FROM Orders@BG_LINK;
Row counts: compare SELECT COUNT(*). Check aggregates like SUM(total_amount).Hash columns for spot checks.
Split exports by date, leverage parallel SQL*Loader, disable indexes/constraints during bulk loads, and enable Oracle Direct Path.
Rebuild indexes, gather statistics (DBMS_STATS), recreate views, and port UDFs to PL/SQL.
STRING → VARCHAR2(4000), BYTES → RAW, NUMERIC → NUMBER(38,9), BOOL → NUMBER(1), DATE → DATE, STRUCT → JSON.
Create matching Oracle Range or Interval partitions, export each BigQuery partition to its own file, and load in parallel.
CREATE TABLE Orders (
...
) PARTITION BY RANGE (order_date) (
PARTITION p2023 VALUES LESS THAN (DATE '2024-01-01'),
PARTITION pmax VALUES LESS THAN (MAXVALUE)
);
Wrap export, upload, and load steps in Cloud Build or Airflow, passing file lists to SQL*Loader via templates.
Encrypt files in transit (gsutil --sse), restrict GCS access, and purge stage files after load.In Oracle, load into staging schema with limited privileges.
Increase SQL*Loader PARALLEL, use DIRECT=TRUE, and adjust Oracle PGA_AGGREGATE_LIMIT to sustain throughput.
Track Cloud Storage object counters, SQL*Loader log files, and Oracle v$session_longops to estimate time remaining.
.
Yes. Schedule daily exports of changed partitions or use Oracle GoldenGate for BigQuery to replicate CDC streams.
Convert BigQuery views to Oracle views manually; translate JavaScript UDFs into PL/SQL functions. Test with sample rows.
No. Export snapshots, backfill, then switch applications to Oracle once validation passes. Use incremental loads for last-minute changes.