Database & Data Management · head to head
BigQuery vs Google Cloud SQL
BigQuery
Database & Data Management
Serverless, highly scalable enterprise data warehouse
- From
- Free
- Rated
- -
Google Cloud SQL
Database & Data Management
Fully managed relational database service for MySQL, PostgreSQL, and SQL Server
- From
- Free
- Rated
- -
The short version
- Each has a real cost: BigQuery query costs can become substantial for organizations with high query volumes; Google Cloud SQL locked into Google Cloud ecosystem with limited cross-cloud portability
- They diverge on capability: BigQuery covers Serverless Architecture, Google Cloud SQL covers High Availability.
Where they differ
Only the attributes on which BigQuery and Google Cloud SQL actually diverge.
| Attribute | BigQuery | Google Cloud SQL |
|---|---|---|
| Platforms | Web, Cloud API | Google Cloud Platform |
Identical on both: starting price (Free), pricing model (usage-based), free tier (Yes), user rating (Not yet rated), category (Database & Data Management), founded (2008).
What each one covers
Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.
Only in BigQuery
- Serverless Architecture
- Petabyte Scale
- Real-time Analytics
- Machine Learning
- Geospatial Analysis
- Streaming Ingestion
- Standard SQL
- Looker
Only in Google Cloud SQL
- High Availability
- Automated Backups
- Point-in-time Recovery
- Encryption
- Regional/Zonal Instances
- Read Replicas
- Private IP
- BigQuery
Both cover
- Dataflow
- Web support
- Gcp support
What people use each for
The jobs each tool is most often brought in to do.
BigQuery
- Business intelligencenot Google Cloud SQL
- Data warehousingnot Google Cloud SQL
- Real-time analyticsnot Google Cloud SQL
- Reporting
- Machine learningnot Google Cloud SQL
Google Cloud SQL
- Transaction processingnot BigQuery
- Data storagenot BigQuery
- Application backendnot BigQuery
- Reporting
- Data analyticsnot BigQuery
Both are used for reporting, on those jobs the choice comes down to price and fit rather than capability.
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
BigQuery
- Query costs can become substantial for organizations with high query volumes
- Data egress from Google Cloud incurs additional charges
Google Cloud SQL
- Locked into Google Cloud ecosystem with limited cross-cloud portability
- Pay-as-you-go pricing can become expensive with unpredictable workloads
- Limited customization options compared to self-managed databases
Pricing, plan by plan
BigQuery
Free- Free TierFree
- 1TB queries/month
- 10GB storage/month
- Standard support
- On-demand$6.25/TB
- Pay per query
- Pay per storage
- All features
Google Cloud SQL
Free- Free TierFree
- db-f1-micro instance
- 30GB storage
- Limited usage
- Standard$25/month
- High availability
- Automated backups
- Point-in-time recovery
Which should you pick?
Choose BigQuery if
- You need serverless architecture.
- You want to start without paying.
- You work on Web, Cloud API.
- You also want petabyte scale.
Choose Google Cloud SQL if
- You need high availability.
- You want to start without paying.
- You work on Google Cloud Platform.
- You also want automated backups.
Questions people ask
- Is BigQuery or Google Cloud SQL better?
- Neither clearly leads. BigQuery starts at Free and Google Cloud SQL at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, BigQuery or Google Cloud SQL?
- BigQuery starts at Free and Google Cloud SQL at Free.
- Does BigQuery or Google Cloud SQL run on more platforms?
- BigQuery runs on Web, Cloud API. Google Cloud SQL runs on Google Cloud Platform.
- Can I use BigQuery for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is BigQuery best used for?
- BigQuery is most often used for business intelligence, data warehousing, real-time analytics, reporting. Of those, business intelligence and data warehousing are not what Google Cloud SQL is typically brought in for.
- What can BigQuery do that Google Cloud SQL cannot?
- BigQuery covers Serverless Architecture, Petabyte Scale, Real-time Analytics, Machine Learning. Google Cloud SQL covers High Availability, Automated Backups, Point-in-time Recovery, Encryption. Both handle Dataflow, Web support, Gcp support.
Answered from the vendors’ own pages
BigQuery: How is BigQuery priced?
BigQuery charges $5 per terabyte of data processed in on-demand queries. Storage is billed separately: active storage is charged per GB, and data inactive for 90+ days moves to long-term storage at reduced rates.
SourceGoogle Cloud SQL: What database engines does Google Cloud SQL support?
Google Cloud SQL supports MySQL, PostgreSQL, and SQL Server. Users can choose their preferred engine when provisioning an instance and Google handles automated backups, replication, patching, and scaling.
SourceBigQuery: What is BigQuery's architecture?
BigQuery separates compute and storage, using Google's Colossus for distributed storage and Borg for computation, allowing independent scaling of each.
SourceGoogle Cloud SQL: Does Google Cloud SQL have a free tier?
Google Cloud SQL does not have a free tier, though new users receive free trial credits from Google Cloud Platform. Pricing is based on compute resources (CPU and memory) and storage used, with options for committed use discounts.
SourceGoogle Cloud SQL: Can Google Cloud SQL scale automatically?
Yes. Cloud SQL automatically scales database storage and compute resources to handle increased workloads without manual intervention, and includes automated backups and high availability configurations.
Source