Oracle Data Warehouse to BigQuery Migration
Migrate Oracle DW to BigQuery with 85% cost savings, 10x faster queries, and zero downtime. Complete migration in 4-6 weeks with AI-powered automation.
Complete Oracle DW Migration Scope
Data Objects
ETL & Processing
Analytics & BI
Security & Governance
4-Phase Migration Process
Assessment & Planning
Analyze Oracle DW environment and create detailed migration plan.
Activities:
- • Schema analysis and complexity assessment
- • PL/SQL code inventory and conversion planning
- • Query workload analysis and optimization
- • BigQuery architecture design
Deliverables:
- • Migration assessment report
- • BigQuery schema design
- • Code conversion strategy
- • Project timeline and resource plan
Schema & Code Conversion
Convert Oracle schemas and PL/SQL code to BigQuery-compatible format.
Activities:
- • Automated schema conversion
- • PL/SQL to SQL/JavaScript conversion
- • Query optimization for BigQuery
- • ETL pipeline modernization
Deliverables:
- • BigQuery schemas created
- • Converted stored procedures
- • Optimized queries
- • Modern ETL pipelines
Data Migration & Validation
Migrate data from Oracle to BigQuery with comprehensive validation.
Activities:
- • Initial data load to BigQuery
- • Incremental sync setup
- • Row count and checksum validation
- • Query result comparison
Deliverables:
- • Complete data in BigQuery
- • Real-time sync operational
- • Validation reports (99.99% accuracy)
- • Performance benchmarks
Cutover & Optimization
Switch to BigQuery and optimize for performance and cost.
Activities:
- • Application cutover to BigQuery
- • Query performance optimization
- • Cost optimization (partitioning, clustering)
- • Monitoring and alerting setup
Deliverables:
- • Production cutover complete
- • Optimized query performance
- • Cost optimization implemented
- • Operations documentation
Oracle DW vs BigQuery Comparison
| Factor | Oracle DW | BigQuery |
|---|---|---|
| Licensing Cost | $47,500/core/year + support | $5/TB storage + $5/TB query |
| Query Performance | Minutes for complex queries | Seconds - 10x faster |
| Scalability | Manual scaling, downtime required | Auto-scaling, petabyte-scale |
| Maintenance | High - patching, tuning, backups | Zero - fully managed |
| Data Loading | Slow - hours for large datasets | Fast - streaming ingestion |
| ML Integration | Limited - requires external tools | Native - BigQuery ML built-in |
| Disaster Recovery | Manual setup, additional cost | Automatic - multi-region replication |
| Total 3-Year TCO | $2.5M (10TB, 100 users) | $375K - 85% savings |
People Also Ask
Can PL/SQL code be converted to BigQuery?
Yes, PL/SQL code can be converted to BigQuery using two approaches: SQL conversion for simple procedures (converted to BigQuery SQL with scripting), and JavaScript UDFs for complex logic (converted to JavaScript user-defined functions). AI-powered conversion achieves 95% automation for standard PL/SQL patterns including cursors, loops, exception handling, and dynamic SQL. Complex business logic may require manual review, but the AI provides detailed conversion reports highlighting areas needing attention. Most organizations complete PL/SQL conversion in 1-2 weeks.
How do you handle Oracle-specific features in BigQuery?
Oracle-specific features are handled through equivalent BigQuery capabilities: Materialized views become BigQuery materialized views with automatic refresh, partitioning becomes BigQuery partitioning and clustering for performance, sequences become GENERATE_UUID() or auto-increment columns, synonyms become views or dataset references, and packages become organized sets of stored procedures. Some features like database links require architectural changes to use BigQuery federated queries or data transfer services. AI migration automatically identifies Oracle-specific features and recommends BigQuery equivalents.
What about BI tools connected to Oracle?
BI tools connected to Oracle can easily connect to BigQuery using native connectors available for Tableau, Power BI, Looker, Qlik, and other major BI platforms. The migration process includes updating connection strings to point to BigQuery, converting Oracle-specific SQL in reports to BigQuery SQL, testing all reports and dashboards for accuracy, and optimizing queries for BigQuery's columnar architecture. Most BI tools support BigQuery natively with better performance than Oracle. AI migration automatically converts report queries and validates results match Oracle output.
How long does Oracle to BigQuery migration take?
Oracle to BigQuery migration typically takes 4-6 weeks with AI-powered automation: Week 1 for assessment and planning, Weeks 2-3 for schema and code conversion, Weeks 3-5 for data migration and validation, and Week 6 for cutover and optimization. Traditional manual migrations take 3-6 months. Timeline depends on data volume (TB to PB scale), code complexity (number of PL/SQL procedures), number of BI reports and applications, and testing requirements. AI automation reduces migration time by 75% while ensuring 99.99% accuracy.
What are the cost savings of migrating to BigQuery?
BigQuery provides 85% cost savings compared to Oracle DW through eliminated licensing costs (no per-core fees), zero infrastructure management (no hardware, patching, or DBA costs), pay-per-query pricing (only pay for queries run, not idle capacity), automatic optimization (no manual tuning required), and reduced disaster recovery costs (built-in multi-region replication). For a typical 10TB data warehouse with 100 users, 3-year TCO is $375K for BigQuery vs $2.5M for Oracle. Most organizations achieve ROI within 6-12 months and save $500K-$2M annually.
Ready to Migrate from Oracle to BigQuery?
Get 85% cost savings, 10x faster queries, and zero downtime with AI-powered migration.