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Databases · head to head

Couchbase vs Apache Spark MLlib

Couchbase logo

Couchbase

Databases

The modern database for enterprise applications

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: Couchbase the free tier is a single node with 8 GB of storage and forum support only; 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: Couchbase covers JSON Document Model, Apache Spark MLlib covers Classification.

Where they differ

Only the attributes on which Couchbase and Apache Spark MLlib actually diverge.

Attributes where Couchbase and Apache Spark MLlib differ
AttributeCouchbaseApache Spark MLlib
Pricing modelfreemiumopen-source
PlatformsLinux, Windows, Mac, Docker, WebLinux, macOS, Windows
CategoryDatabasesMachine Learning
Founded20111999

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 Couchbase

  • JSON Document Model
  • SQL++ Query
  • Full-text Search
  • Eventing
  • Analytics
  • Mobile Sync
  • Multi-dimensional Scaling
  • Spark

Only in Apache Spark MLlib

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

Both cover

  • Kafka
  • Linux support
  • Windows support
  • Mac support

What people use each for

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

Couchbase

  • Running a distributed NoSQL document database as a managed servicenot Apache Spark MLlib
  • Mobile sync and offline first applications backed by a cloud databasenot Apache Spark MLlib

Apache Spark MLlib

  • Machine learningnot Couchbase
  • Data sciencenot Couchbase
  • Distributed computingnot Couchbase

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Couchbase

  • The free tier is a single node with 8 GB of storage and forum support only
  • Node rates are hourly and quoted as starting figures, from $0.15 an hour on Basic to $0.49 on Enterprise
  • The Developer Pro and Enterprise plans require 3 nodes, so the hourly rate multiplies before any usage
  • Backup storage is billed separately at $0.07 per GB a month, and analytics backups at $0.14
  • Support response time is a plan feature, at 8 hours on Developer Pro against 30 minutes on Enterprise
  • AI and analytics run as separately priced planes at up to $0.86 an hour per node

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

Couchbase

Free
  • CommunityFree
    • Full features
    • Community support
    • Self-managed
  • Capella FreeFree
    • Managed service
    • Limited resources
    • Cloud hosted

Apache Spark MLlib

Free

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

Which should you pick?

Choose Couchbase if

  • You need json document model.
  • You want to start without paying.
  • You work on Linux, Windows, Mac, Docker, Web.
  • You also want sql++ query.
Couchbase 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 Couchbase or Apache Spark MLlib better?
Neither clearly leads. Couchbase 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, Couchbase or Apache Spark MLlib?
Couchbase starts at Free and Apache Spark MLlib at Free.
Does Couchbase or Apache Spark MLlib run on more platforms?
Couchbase runs on Linux, Windows, Mac, Docker, Web. Apache Spark MLlib runs on Linux, macOS, Windows.
Can I use Couchbase for free?
Both have a free tier, so you can try either at no cost before committing.
What is Couchbase best used for?
Couchbase is most often used for running a distributed nosql document database as a managed service, mobile sync and offline first applications backed by a cloud database. Of those, running a distributed nosql document database as a managed service and mobile sync and offline first applications backed by a cloud database are not what Apache Spark MLlib is typically brought in for.
What can Couchbase do that Apache Spark MLlib cannot?
Couchbase covers JSON Document Model, SQL++ Query, Full-text Search, Eventing. Apache Spark MLlib covers Classification, Regression, Clustering, Collaborative filtering. Both handle Kafka, Linux support, Windows support, Mac support.

Answered from the vendors’ own pages

Couchbase: Does Couchbase offer a free tier?

Yes, Couchbase offers a free tier option. Users can start for free from the main website.

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
Couchbase: How do I access Couchbase pricing details?

Couchbase maintains a dedicated pricing page, but detailed tier information and costs are not available on the homepage. You can visit the pricing page or contact their sales team.

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
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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