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Machine Learning · head to head

KNIME vs Pachyderm

KNIME logo

KNIME

Machine Learning

Open source data analytics and integration platform

From
Free
Rated
-
Full reviewWebsite
P

Pachyderm

Machine Learning

Data versioning and container pipelines that run on your Kubernetes cluster

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: KNIME the free Analytics Platform runs locally only, so anything shared or scheduled requires a paid Hub; Pachyderm it runs only on Kubernetes, so operating it means someone who can debug pods, storage classes and node pressure, and on a team without that person a cluster problem and an ML outage are the same event.
  • They diverge on capability: KNIME covers Visual workflows, Pachyderm covers Versioned file system.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which KNIME and Pachyderm actually diverge.

Attributes where KNIME and Pachyderm differ
AttributeKNIMEPachyderm
PlatformsLinux, Mac, WindowsLinux
Founded20042014

Identical on both: starting price (Free), pricing model (freemium), free tier (Yes), user rating (Not yet rated), category (Machine Learning).

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 KNIME

  • Visual workflows
  • Data preprocessing
  • Machine learning
  • Visualization
  • Reporting
  • Python
  • R
  • Spark

Only in Pachyderm

  • Versioned file system
  • Datum-based incremental processing
  • Container pipelines
  • Automatic provenance
  • Parallel execution
  • S3 gateway
  • Enterprise authentication
  • Object storage backends

What people use each for

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

KNIME

  • Data science and machine learning workflowsnot Pachyderm
  • ETL and data pipeline automationnot Pachyderm
  • Predictive analytics and modelingnot Pachyderm

Pachyderm

  • Reprocessing a growing archive of images or documents where a full pass every night would be wasteful and only the new files matternot KNIME
  • Regulated pipelines where an auditor will ask which exact input files and which code version produced a given resultnot KNIME
  • Genomics and scientific workflows built from existing command line tools that are easier to containerise than to rewritenot KNIME
  • Teams that already run Kubernetes and want data lineage without adopting a full commercial ML platformnot KNIME

Where each one falls short

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

KNIME

  • The free Analytics Platform runs locally only, so anything shared or scheduled requires a paid Hub
  • The free AI assistant is limited to 20 interactions a month
  • Paid workflow runtime is metered in credits, with 120 included on Pro and overage at $0.025 per vCore minute
  • The Team plan at $99 a month includes 3 members, with additional seats at $49 a month each
  • Business Hub pricing is on request, and its tiers are capped at 4, 8 and 16 vCores with 5, 5 and 20 users

Pachyderm

  • It runs only on Kubernetes, so operating it means someone who can debug pods, storage classes and node pressure, and on a team without that person a cluster problem and an ML outage are the same event.
  • Data is held in Pachyderm's content-addressed repositories rather than as plain files in a bucket, so every other tool reaches it through the client or the S3 gateway and migrating away is a full export rather than a redirect.
  • The glob pattern that decides the unit of parallel work is the most consequential line in a pipeline specification, and getting it wrong produces either one enormous serial job or millions of tiny ones whose container start-up dominates the runtime.
  • Compute is billed by your cloud provider, not by Pachyderm, so a platform that looks inexpensive on the licence line runs on a cluster that has to be sized for peak pipeline load and, for training work, carries GPU nodes.
  • The project's direction now sits inside a large hardware vendor's portfolio following the 2023 acquisition, and a team adopting the community edition has no contractual claim on its continued development.

Pricing, plan by plan

KNIME

Free
  • Analytics PlatformFree
    • 300+ data sources
    • Unlimited local processing
    • K-AI assistant (20 interactions/month)
  • Pro$19/month
    • 120 workflow runtime credits
    • Data app deployment
    • K-AI (500 interactions/month)
  • Team$99/month
    • All Pro features
    • Collaboration spaces for up to 3 team members
    • Additional members: $49/month each
  • Business Hub$null/month
    • Enterprise automation and governance
    • LDAP/OAuth authentication
    • Staged deployment

Pachyderm

Free
  • CommunityFree
    • Core features
    • Community support
  • EnterpriseFree
    • Advanced security
    • Premium support
    • SLAs

Which should you pick?

Choose KNIME if

  • You need visual workflows.
  • You want to start without paying.
  • You work on Linux, Mac, Windows.
  • You also want data preprocessing.
KNIME review

Choose Pachyderm if

  • You need versioned file system.
  • You want to start without paying.
  • You work on Linux.
  • You also want datum-based incremental processing.
Pachyderm review

Questions people ask

Is KNIME or Pachyderm better?
Neither clearly leads. KNIME starts at Free and Pachyderm at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, KNIME or Pachyderm?
KNIME starts at Free and Pachyderm at Free.
Does KNIME or Pachyderm run on more platforms?
KNIME runs on Linux, Mac, Windows. Pachyderm runs on Linux.
Can I use KNIME for free?
Both have a free tier, so you can try either at no cost before committing.
What is KNIME best used for?
KNIME is most often used for data science and machine learning workflows, etl and data pipeline automation, predictive analytics and modeling. Of those, data science and machine learning workflows and etl and data pipeline automation are not what Pachyderm is typically brought in for.
What can KNIME do that Pachyderm cannot?
KNIME covers Visual workflows, Data preprocessing, Machine learning, Visualization. Pachyderm covers Versioned file system, Datum-based incremental processing, Container pipelines, Automatic provenance.

Answered from the vendors’ own pages

KNIME: Is KNIME free?

Yes, KNIME Analytics Platform is free with 300+ data sources, unlimited local processing, and 20 K-AI assistant interactions per month.

Source
Pachyderm: Is Pachyderm open source?

The community edition is, under Apache 2.0. Authentication, role-based access control, the console and multi-tenancy sit behind an enterprise licence key, which is the set of features most organisations need once more than one team uses it.

KNIME: What do KNIME paid plans cost?

Pro plan starts at $19/month with 120 runtime credits. Team plan starts at $99/month for up to 3 members, with additional members at $49/month each.

Source
Pachyderm: Do I need Kubernetes to run it?

Yes. There is no non-Kubernetes deployment. A local single-node install exists for evaluation, but anything real is a cluster with object storage behind it.

KNIME: What is KNIME's runtime credit system?

Pro and Team plans include runtime credits for workflow execution. Additional runtime beyond included credits costs $0.025 per vCore minute.

Source
Pachyderm: How is it different from DVC?

DVC is a command line tool a person runs alongside Git, with no server. Pachyderm is a server that owns the data and schedules the work centrally. DVC records what you did; Pachyderm does it and records it.

KNIME: Does KNIME offer enterprise pricing?

Yes, Business Hub is available for enterprises needing automation, governance, LDAP/OAuth auth, and dedicated resources. Pricing available on request.

Source
Pachyderm: What does it actually cost to run?

The licence is separate from the infrastructure. You pay your cloud provider for the Kubernetes nodes that run every pipeline pod and for the object storage holding every version of every data set, and that bill grows with history as well as with size.

Pachyderm: Can I serve models with it?

No. It is a batch data and training pipeline system. Serving is a separate tool and a separate deployment.

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