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Databases · head to head

Google Cloud SQL vs Apache Spark MLlib

Google Cloud SQL logo

Google Cloud SQL

Databases

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

From
Free
Rated
-
Full reviewWebsite
Apache Spark MLlib logo

Apache Spark MLlib

Machine Learning

Scalable machine learning on Apache Spark

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Google Cloud SQL locked into Google Cloud ecosystem with limited cross-cloud portability; Apache Spark MLlib apache Spark MLlib is Apache 2.0 licensed and free with no paid tier from the Apache project itself; SLA-backed support has to be sourced from a third party such as a managed Spark vendor rather than from Apache.
  • They diverge on capability: Google Cloud SQL covers High Availability, Apache Spark MLlib covers Classification.

Where they differ

Only the attributes on which Google Cloud SQL and Apache Spark MLlib actually diverge.

Attributes where Google Cloud SQL and Apache Spark MLlib differ
AttributeGoogle Cloud SQLApache Spark MLlib
Pricing modelusage-basedopen-source
PlatformsGoogle Cloud PlatformLinux, macOS, Windows
CategoryDatabasesMachine Learning
Founded20081999

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
  • BigQuery

Only in Apache Spark MLlib

  • Classification
  • Regression
  • Clustering
  • Collaborative filtering
  • Feature engineering
  • Apache Spark
  • Hadoop
  • Kafka

What people use each for

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

Google Cloud SQL

  • Transaction processingnot Apache Spark MLlib
  • Data storagenot Apache Spark MLlib
  • Application backendnot Apache Spark MLlib
  • Reportingnot Apache Spark MLlib
  • Data analyticsnot Apache Spark MLlib

Apache Spark MLlib

  • Machine learningnot Google Cloud SQL
  • Data sciencenot Google Cloud SQL
  • Distributed computingnot 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

Apache Spark MLlib

  • Apache Spark MLlib is Apache 2.0 licensed and free with no paid tier from the Apache project itself; SLA-backed support has to be sourced from a third party such as a managed Spark vendor rather than from Apache.

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

Apache Spark MLlib

Free

No published plan breakdown. See the Apache Spark MLlib review.

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.
Google Cloud SQL review

Choose Apache Spark MLlib if

  • You need classification.
  • You want to start without paying.
  • You work on Linux, macOS, Windows.
  • You also want regression.
Apache Spark MLlib review

Questions people ask

Is Google Cloud SQL or Apache Spark MLlib better?
Neither clearly leads. Google Cloud SQL starts at Free and Apache Spark MLlib at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Google Cloud SQL or Apache Spark MLlib?
Google Cloud SQL starts at Free and Apache Spark MLlib at Free.
Does Google Cloud SQL or Apache Spark MLlib run on more platforms?
Google Cloud SQL runs on Google Cloud Platform. Apache Spark MLlib runs on Linux, macOS, Windows.
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 Apache Spark MLlib is typically brought in for.
What can Google Cloud SQL do that Apache Spark MLlib cannot?
Google Cloud SQL covers High Availability, Automated Backups, Point-in-time Recovery, Encryption. Apache Spark MLlib covers Classification, Regression, Clustering, Collaborative filtering.

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
Apache Spark MLlib: How much does Apache Spark MLlib cost?

MLlib is completely free and open source, licensed under the Apache License Version 2.0. There are no subscription, licensing, or usage fees.

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
Apache Spark MLlib: What licensing does MLlib use?

MLlib is licensed under Apache License Version 2.0, making it freely available for all users regardless of organization size or use case.

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
Apache Spark MLlib: How do I use MLlib?

MLlib is built into Apache Spark. Download Spark, which includes MLlib as a module, and deploy on your choice of infrastructure including Hadoop, Mesos, Kubernetes, standalone, or cloud.

Source
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