Amazon Aurora vs BigQuery

AWS's database that makes you feel fancy without the price tag of Oracle, but still costs more than your rent meets google's data warehouse that makes querying petabytes feel like a casual stroll, as long as you don't mind the bill. Here's our take.

Amazon Aurora

Nice Pick

AWS's database that makes you feel fancy without the price tag of Oracle, but still costs more than your rent.

Pros

• Fully managed with automatic scaling, backups, and patching
• Up to 5x MySQL and 3x PostgreSQL performance with cloud-optimized storage
• High availability and durability through multi-AZ replication
• MySQL and PostgreSQL compatibility for easy migration

Cons

• Can get expensive quickly with scaling and I/O costs
• Vendor lock-in to AWS ecosystem
• Limited to AWS regions, which might affect latency for global apps

BigQuery

Google's data warehouse that makes querying petabytes feel like a casual stroll, as long as you don't mind the bill.

Pros

• Serverless architecture means zero infrastructure management
• Blazing-fast SQL queries on massive datasets with Google's distributed processing
• Built-in machine learning and seamless integration with Google Cloud services

Cons

• Costs can spiral quickly with complex queries or large data scans
• Limited control over performance tuning compared to self-managed warehouses

The Verdict

Use Amazon Aurora if: You want fully managed with automatic scaling, backups, and patching and can live with can get expensive quickly with scaling and i/o costs.

Use BigQuery if: You prioritize serverless architecture means zero infrastructure management over what Amazon Aurora offers.

The Bottom Line

Amazon Aurora wins

AWS's database that makes you feel fancy without the price tag of Oracle, but still costs more than your rent.