How to Migrate from MariaDB to BigQuery

How do I migrate a MariaDB database to BigQuery?

Export MariaDB data, transform it to BigQuery-compatible formats, and load it into BigQuery tables while preserving schema and relationships.

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Description

Example H2

Example H3

Why move from MariaDB to BigQuery?

BigQuery offers serverless scaling, lower ops overhead, and native analytics. Migrating frees teams from manual sharding and lets them query terabytes with ANSI SQL.

What are the main migration steps?

Extract data, convert schema, load into BigQuery, validate results, and switch applications. Following a repeatable pipeline prevents data loss.

Step 1 – How do I extract data from MariaDB?

Use mysqldump --tab for each table to produce .sql (DDL) and .txt (TSV) files. This keeps schema and data separate, easing type mapping.

Step 2 – How do I convert the schema?

Edit the generated .sql to match BigQuery types: INT → INT64, DATETIME → DATETIME, DECIMAL → NUMERIC. Save as schema.json for each table.

Step 3 – How do I load data into BigQuery fast?

Create a dataset, then run bq load --source_format=CSV --skip_leading_rows=0 for every file. Load jobs can run in parallel to cut total time.

Step 4 – How do I verify row counts?

Compare SELECT COUNT(*) results in MariaDB and BigQuery. Small mismatches usually mean unescaped delimiters or wrong null handling.

Step 5 – How do I switch my application?

Update connection strings, rewrite joins using fully qualified table names like project.dataset.Customers, and retest critical paths.

What are best practices for large tables?

Chunk exports by primary key range, compress files with gzip, and load to partitioned tables in BigQuery to keep query costs low.

How can I automate future syncs?

Schedule nightly exports in MariaDB, push files to Cloud Storage, and trigger a Cloud Function that calls bq load. This builds an incremental pipeline.

Why How to Migrate from MariaDB to BigQuery is important

How to Migrate from MariaDB to BigQuery Example Usage


-- Verify migration of high-value orders
SELECT o.id,
       c.name,
       o.total_amount
FROM   `ecommerce.Orders` o
JOIN   `ecommerce.Customers` c ON c.id = o.customer_id
WHERE  o.total_amount > 500
ORDER  BY o.total_amount DESC;

How to Migrate from MariaDB to BigQuery Syntax


# Export schema and data from MariaDB
mysqldump -uUSER -pPASS --tab=/tmp/export \
  --fields-terminated-by="," \
  --fields-enclosed-by='"' \
  --lines-terminated-by="\n" \
  ecommerce Customers Orders Products OrderItems

# Create dataset in BigQuery
bq --location=US mk --dataset ecommerce

# Load Customers into BigQuery
gsutil cp /tmp/export/Customers.txt gs://my-bucket/Customers.csv
bq load \
  --source_format=CSV \
  --skip_leading_rows=0 \
  --replace \
  ecommerce.Customers \
  gs://my-bucket/Customers.csv \
  id:INT64,name:STRING,email:STRING,created_at:DATETIME

# Repeat bq load for Orders, Products, OrderItems

Common Mistakes

Ignoring data types. Directly loading MariaDB CSVs without a JSON schema makes BigQuery guess types, often storing numbers as STRING. Always supply an explicit schema file.
Skipping NULL handling. MariaDB writes \N for NULL; BigQuery expects empty fields. Use --fields-escaped-by to prevent literal \N strings or transform files before loading.