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Flagsmith vs Apache Spark MLlib

Flagsmith logo

Flagsmith

Software Development

Open-source feature flag and remote config platform

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: Flagsmith the Free plan supports only a single team member, limiting collaboration for small teams.; 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: Flagsmith covers Feature flags, Apache Spark MLlib covers Classification.

Where they differ

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

Attributes where Flagsmith and Apache Spark MLlib differ
AttributeFlagsmithApache Spark MLlib
Pricing modelfreemiumopen-source
Platformsweb, apiLinux, macOS, Windows
CategorySoftware DevelopmentMachine Learning
FoundedUnknown1999

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 Flagsmith

  • Feature flags
  • Segments
  • A/B testing
  • Scheduled flags
  • SDKs
  • SAML/SSO

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.

Flagsmith

  • Gradual feature rollouts across environmentsnot Apache Spark MLlib
  • Remote configuration without redeploying codenot Apache Spark MLlib
  • Running A/B tests tied to feature flagsnot Apache Spark MLlib
  • Self-hosting feature flags for data residency requirementsnot Apache Spark MLlib

Apache Spark MLlib

  • Machine learningnot Flagsmith
  • Data sciencenot Flagsmith
  • Distributed computingnot Flagsmith

Where each one falls short

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

Flagsmith

  • The Free plan supports only a single team member, limiting collaboration for small teams.
  • Exceeding request limits triggers overage charges after a one-time 30-day grace period.
  • Enterprise-grade SSO and governance are locked behind the Scale-Up and Enterprise tiers.
  • Self-hosting requires operating and updating the platform yourself, unlike a fully managed SaaS competitor.

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

Flagsmith

Free
  • FreeFree
    • Up to 50,000 requests/month
    • 1 team member
    • Unlimited feature flags, environments, identities and segments
  • Start-Up$45/month
    • Up to 1,000,000 requests/month
    • 3 team members
    • Scheduled flags, 2FA, A/B testing, integrations, email support
  • Scale-Up$300/month
    • 5,000,000+ requests/month
    • 5-20 team members
    • SAML/SSO, governance features, priority support

Apache Spark MLlib

Free

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

Which should you pick?

Choose Flagsmith if

  • You need feature flags.
  • You want to start without paying.
  • You work on web, api.
  • You also want segments.
Flagsmith 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 Flagsmith or Apache Spark MLlib better?
Neither clearly leads. Flagsmith 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, Flagsmith or Apache Spark MLlib?
Flagsmith starts at Free and Apache Spark MLlib at Free.
Does Flagsmith or Apache Spark MLlib run on more platforms?
Flagsmith runs on web, api. Apache Spark MLlib runs on Linux, macOS, Windows.
Can I use Flagsmith for free?
Both have a free tier, so you can try either at no cost before committing.
What is Flagsmith best used for?
Flagsmith is most often used for gradual feature rollouts across environments, remote configuration without redeploying code, running a/b tests tied to feature flags, self-hosting feature flags for data residency requirements. Of those, gradual feature rollouts across environments and remote configuration without redeploying code are not what Apache Spark MLlib is typically brought in for.
What can Flagsmith do that Apache Spark MLlib cannot?
Flagsmith covers Feature flags, Segments, A/B testing, Scheduled flags. Apache Spark MLlib covers Classification, Regression, Clustering, Collaborative filtering.

Answered from the vendors’ own pages

Flagsmith: What does Flagsmith cost?

Flagsmith has a Free plan, a Start-Up plan from $40-45/month, a Scale-Up plan from $250-300/month, and custom Enterprise pricing.

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
Flagsmith: Is there a free plan, and what are its limits?

The Free plan supports up to 50,000 requests per month and 1 team member, with unlimited feature flags, environments, identities and segments.

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
Flagsmith: How is usage metered?

Usage is metered by monthly API requests; exceeding a plan's limit triggers overage charges starting around $50 per million requests, with a 30-day grace period the first time a paid plan exceeds its limit.

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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