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Business Intelligence · head to head

Mode vs Palantir Foundry

Mode logo

Mode

Business Intelligence

Collaborative analytics for data teams

From
Free
Rated
-
Full reviewWebsite
Palantir Foundry logo

Palantir Foundry

Machine Learning

Operating system for modern enterprise

From
On request
Rated
-
Full reviewWebsite

The short version

  • Only Mode has a free tier, so it costs nothing to try first.
  • Each has a real cost: Mode free tier limited to 4GB RAM and 1 CPU for SQL notebooks, insufficient for large datasets; Palantir Foundry custom pricing model with no public information makes budgeting difficult
  • They diverge on capability: Mode covers SQL Editor, Palantir Foundry covers Data integration.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Mode and Palantir Foundry actually diverge.

Attributes where Mode and Palantir Foundry differ
AttributeModePalantir Foundry
Starting priceFreeOn request
Free tierYesNo
CategoryBusiness IntelligenceMachine Learning
Founded20132003

Identical on both: pricing model (subscription), platforms (Web), 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 Mode

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

Only in Palantir Foundry

  • Data integration
  • Ontology modeling
  • Pipeline builder
  • Operational analytics
  • Governance
  • Enterprise systems
  • Cloud platforms
  • IoT

Both cover

  • Web support

What people use each for

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

Mode

  • Self-service analyticsnot Palantir Foundry
  • Data explorationnot Palantir Foundry
  • Ad-hoc reportingnot Palantir Foundry
  • Collaborative analysisnot Palantir Foundry
  • Embedded analyticsnot Palantir Foundry

Palantir Foundry

  • Machine learningnot Mode
  • Data analysisnot Mode
  • Model trainingnot Mode
  • Predictive analyticsnot Mode

Where each one falls short

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

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

Palantir Foundry

  • Custom pricing model with no public information makes budgeting difficult
  • Steep implementation and configuration requirements
  • Requires significant technical expertise to operate effectively
  • Long sales cycle typical for enterprise software

Pricing, plan by plan

Mode

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

Palantir Foundry

On request
  • EnterpriseFree
    • Full platform
    • Custom deployment
    • Enterprise support

Which should you pick?

Choose Mode if

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

Choose Palantir Foundry if

  • You need data integration.
  • You also want ontology modeling.
Palantir Foundry review

Questions people ask

Is Mode or Palantir Foundry better?
Neither clearly leads. Mode starts at Free and Palantir Foundry at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Mode or Palantir Foundry?
Mode has a free tier; the other does not. Paid plans start at Free for Mode and On request for Palantir Foundry.
Does Mode or Palantir Foundry run on more platforms?
Both run on Web, so platform support will not decide this one for you.
Can I use Mode for free?
Yes. Mode has a free tier, so you can try it without paying. Palantir Foundry starts at On request.
What is Mode best used for?
Mode is most often used for self-service analytics, data exploration, ad-hoc reporting, collaborative analysis. Of those, self-service analytics and data exploration are not what Palantir Foundry is typically brought in for.
What can Mode do that Palantir Foundry cannot?
Mode covers SQL Editor, Python/R Notebooks, Interactive Reports, Version Control. Palantir Foundry covers Data integration, Ontology modeling, Pipeline builder, Operational analytics. Both handle Web support.

Answered from the vendors’ own pages

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
Palantir Foundry: What is Palantir Foundry designed for?

Palantir Foundry is an enterprise data integration and analytics platform supporting end-to-end data pipelines, covering ingestion, processing, pipeline building, monitoring, and creating analytics dashboards with both code and no-code tools.

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
Palantir Foundry: How much does Palantir Foundry cost?

Palantir Foundry uses custom pricing. No public list pricing is available. Enterprise customers and government agencies must contact Palantir directly for formal quotes and licensing terms.

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
Palantir Foundry: Who uses Palantir Foundry?

Palantir Foundry serves enterprise and government organizations needing complex data integration, analytics, and operational intelligence across large-scale data environments.

Source
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