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Databases · head to head

Google Cloud SQL vs Mode

Google Cloud SQL logo

Google Cloud SQL

Databases

Fully managed relational database service for MySQL, PostgreSQL, and SQL Server

From
Free
Rated
-
Mode logo

Mode

Business Intelligence

Collaborative analytics for data teams

From
Free
Rated
-

The short version

  • Each has a real cost: Google Cloud SQL locked into Google Cloud ecosystem with limited cross-cloud portability; Mode free tier limited to 4GB RAM and 1 CPU for SQL notebooks, insufficient for large datasets
  • They diverge on capability: Google Cloud SQL covers High Availability, Mode covers SQL Editor.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Google Cloud SQL and Mode actually diverge.

Attributes where Google Cloud SQL and Mode differ
AttributeGoogle Cloud SQLMode
Pricing modelusage-basedsubscription
PlatformsGoogle Cloud PlatformWeb
CategoryDatabasesBusiness Intelligence
Founded20082013

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated).

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
  • Dataflow

Only in Mode

  • SQL Editor
  • Python/R Notebooks
  • Interactive Reports
  • Version Control
  • Scheduling
  • Snowflake
  • Redshift
  • PostgreSQL

Both cover

  • BigQuery
  • Web support

What people use each for

The jobs each tool is most often brought in to do.

Google Cloud SQL

  • Transaction processingnot Mode
  • Data storagenot Mode
  • Application backendnot Mode
  • Reportingnot Mode
  • Data analyticsnot Mode

Mode

  • Self-service analyticsnot Google Cloud SQL
  • Data explorationnot Google Cloud SQL
  • Ad-hoc reportingnot Google Cloud SQL
  • Collaborative analysisnot Google Cloud SQL
  • Embedded analyticsnot Google Cloud SQL

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

Mode

  • Free tier limited to 4GB RAM and 1 CPU for SQL notebooks, insufficient for large datasets
  • Requires SQL knowledge for most analysis tasks, creating dependency on technical resources
  • Paid plan pricing not publicly listed; requires sales consultation
  • Recently acquired by ThoughtSpot in 2026, creating product direction uncertainty
  • Limited customization options for visual aspects and embedded analytics

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

Mode

Free
  • FreeFree
    • SQL Editor
    • Python/R Notebooks
    • Basic Charts
  • Business$65/month
    • Advanced Visualizations
    • Collaboration
    • Integrations

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 Mode if

  • You need sql editor.
  • You want to start without paying.
  • You also want python/r notebooks.

Questions people ask

Is Google Cloud SQL or Mode better?
Neither clearly leads. Google Cloud SQL starts at Free and Mode at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Google Cloud SQL or Mode?
Google Cloud SQL starts at Free and Mode at Free.
Does Google Cloud SQL or Mode run on more platforms?
Google Cloud SQL runs on Google Cloud Platform. Mode runs on Web.
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 Mode is typically brought in for.
What can Google Cloud SQL do that Mode cannot?
Google Cloud SQL covers High Availability, Automated Backups, Point-in-time Recovery, Encryption. Mode covers SQL Editor, Python/R Notebooks, Interactive Reports, Version Control. Both handle BigQuery, Web 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.

Source
Mode: What languages does Mode support for analysis?

Mode notebooks support SQL, Python (3.11 with pandas, NumPy, scikit-learn, matplotlib), and R (4.2.0 with ggplot2, dplyr, tidyr). Both Python and R allow additional library installation at runtime.

Source
Google 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.

Source
Mode: Can I integrate Mode notebook results into reports?

Yes. Mode allows adding notebook cell results directly to reports, with synchronized scheduling so reports re-run to keep data current.

Source
Google 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
Mode: Does Mode support collaborative analysis?

Yes. Mode notebooks provide moveable code blocks and markdown cells enabling exploratory analysis and team collaboration on data queries and visualizations.

Source
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