Software · head to head
Google Cloud SQL vs BigQuery
Google Cloud SQL
Software
Fully managed relational database service for MySQL, PostgreSQL, and SQL Server
- From
- Free
- Rated
- -
BigQuery
Software
Serverless, highly scalable enterprise data warehouse
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Google Cloud SQL locked into Google Cloud ecosystem with limited cross-cloud portability; BigQuery query costs can become substantial for organizations with high query volumes
- They diverge on capability: Google Cloud SQL covers High Availability, BigQuery covers Serverless Architecture.
Where they differ
Only the attributes on which Google Cloud SQL and BigQuery actually diverge.
| Attribute | Google Cloud SQL | BigQuery |
|---|---|---|
| Platforms | Google Cloud Platform | Web, Cloud API |
Identical on both: starting price (Free), pricing model (usage-based), free tier (Yes), user rating (Not yet rated), category (Unknown), 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 Google Cloud SQL
- High Availability
- Automated Backups
- Point-in-time Recovery
- Encryption
- Regional/Zonal Instances
- Read Replicas
- Private IP
- BigQuery
Only in BigQuery
- Serverless Architecture
- Petabyte Scale
- Real-time Analytics
- Machine Learning
- Geospatial Analysis
- Streaming Ingestion
- Standard SQL
- Looker
Both cover
- Dataflow
- Web support
- Gcp support
What people use each for
The jobs each tool is most often brought in to do.
Google Cloud SQL
- Transaction processingnot BigQuery
- Data storagenot BigQuery
- Application backendnot BigQuery
- Reporting
- Data analyticsnot BigQuery
BigQuery
- Business intelligencenot Google Cloud SQL
- Data warehousingnot Google Cloud SQL
- Real-time analyticsnot Google Cloud SQL
- Reporting
- Machine learningnot Google Cloud SQL
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.
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
BigQuery
- Query costs can become substantial for organizations with high query volumes
- Data egress from Google Cloud incurs additional charges
Pricing, plan by plan
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
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
Which should you pick?
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.
Choose BigQuery if
- You need serverless architecture.
- You want to start without paying.
- You work on Web, Cloud API.
- You also want petabyte scale.
Questions people ask
- Is Google Cloud SQL or BigQuery better?
- Neither clearly leads. Google Cloud SQL starts at Free and BigQuery at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Google Cloud SQL or BigQuery?
- Google Cloud SQL starts at Free and BigQuery at Free.
- Does Google Cloud SQL or BigQuery run on more platforms?
- Google Cloud SQL runs on Google Cloud Platform. BigQuery runs on Web, Cloud API.
- Can I use Google Cloud SQL for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Google Cloud SQL best used for?
- Google Cloud SQL is most often used for transaction processing, data storage, application backend, reporting. Of those, transaction processing and data storage are not what BigQuery is typically brought in for.
- What can Google Cloud SQL do that BigQuery cannot?
- Google Cloud SQL covers High Availability, Automated Backups, Point-in-time Recovery, Encryption. BigQuery covers Serverless Architecture, Petabyte Scale, Real-time Analytics, Machine Learning. Both handle Dataflow, Web support, Gcp support.
Answered from the vendors’ own pages
Google 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: 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: 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.
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: 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