Database & Data Management · head to head
Apache Druid vs Google Cloud SQL
Apache Druid
Database & Data Management
Real-time analytics database for sub-second OLAP queries
- 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: Apache Druid open-source offering lacks high-availability, distributed architecture, and enterprise security features; Google Cloud SQL locked into Google Cloud ecosystem with limited cross-cloud portability
- They diverge on capability: Apache Druid covers Real-time Ingestion, Google Cloud SQL covers High Availability.
Where they differ
Only the attributes on which Apache Druid and Google Cloud SQL actually diverge.
| Attribute | Apache Druid | Google Cloud SQL |
|---|---|---|
| Pricing model | open-source | usage-based |
| Platforms | Docker, Kubernetes, Native deployment (Java-based) | Google Cloud Platform |
| Founded | 1999 | 2008 |
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Database & Data Management).
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 Apache Druid
- Real-time Ingestion
- Sub-second Queries
- Column-oriented Storage
- Streaming Integration
- Approximate Algorithms
- Flexible Schemas
- Time-based Partitioning
- Kafka
Only in Google Cloud SQL
- High Availability
- Automated Backups
- Point-in-time Recovery
- Encryption
- Regional/Zonal Instances
- Read Replicas
- Private IP
- BigQuery
What people use each for
The jobs each tool is most often brought in to do.
Apache Druid
- Real-time analytics platforms ingesting millions of events per second from streaming sourcesnot Google Cloud SQL
- Applications requiring sub-second queries over high-cardinality datasets (billions to trillions of rows)not Google Cloud SQL
- Time-series and event analysis at massive scale with columnar storage efficiencynot Google Cloud SQL
Google Cloud SQL
- Transaction processingnot Apache Druid
- Data storagenot Apache Druid
- Application backendnot Apache Druid
- Reportingnot Apache Druid
- Data analyticsnot Apache Druid
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Apache Druid
- Open-source offering lacks high-availability, distributed architecture, and enterprise security features
- Requires native integration with Apache Kafka or Amazon Kinesis for real-time ingestion; custom integrations need development
- High-concurrency query support (hundreds of thousands QPS) requires significant cluster infrastructure investment
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
Apache Druid
FreeNo published plan breakdown. See the Apache Druid review.
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 Apache Druid if
- You need real-time ingestion.
- You want to start without paying.
- You work on Docker, Kubernetes, Native deployment (Java-based).
- You also want sub-second queries.
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 Apache Druid or Google Cloud SQL better?
- Neither clearly leads. Apache Druid 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, Apache Druid or Google Cloud SQL?
- Apache Druid starts at Free and Google Cloud SQL at Free.
- Does Apache Druid or Google Cloud SQL run on more platforms?
- Apache Druid runs on Docker, Kubernetes, Native deployment (Java-based). Google Cloud SQL runs on Google Cloud Platform.
- Can I use Apache Druid for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Apache Druid best used for?
- Apache Druid is most often used for real-time analytics platforms ingesting millions of events per second from streaming sources, applications requiring sub-second queries over high-cardinality datasets (billions to trillions of rows), time-series and event analysis at massive scale with columnar storage efficiency. Of those, real-time analytics platforms ingesting millions of events per second from streaming sources and applications requiring sub-second queries over high-cardinality datasets (billions to trillions of rows) are not what Google Cloud SQL is typically brought in for.
- What can Apache Druid do that Google Cloud SQL cannot?
- Apache Druid covers Real-time Ingestion, Sub-second Queries, Column-oriented Storage, Streaming Integration. Google Cloud SQL covers High Availability, Automated Backups, Point-in-time Recovery, Encryption.
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.
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