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Business Intelligence · head to head

Cube vs Mode

Cube logo

Cube

Business Intelligence

AI-native analytics platform with semantic layer and governed access

From
Free
Rated
-
Full reviewWebsite
Mode logo

Mode

Business Intelligence

Collaborative analytics for data teams

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Cube per-developer licensing can be expensive for large analytics teams; Mode free tier limited to 4GB RAM and 1 CPU for SQL notebooks, insufficient for large datasets
  • They diverge on capability: Cube covers Analytics Chat, Mode covers SQL Editor.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Cube and Mode actually diverge.

Attributes where Cube and Mode differ
AttributeCubeMode
Pricing modelPer-developer seats with volume pricingsubscription
PlatformsCloud, Self-hostedWeb
FoundedUnknown2013

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Business Intelligence).

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 Cube

  • Analytics Chat
  • Workbooks
  • Dashboards
  • Embedded Analytics
  • AI Integrations
  • Core Data APIs
  • Caching and pre-aggregations

Only in Mode

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

What people use each for

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

Cube

  • Building governed semantic data models for analyticsnot Mode
  • Embedding analytics into customer-facing productsnot Mode
  • Enabling natural language data queries for teamsnot Mode
  • Creating conversational dashboards with AI assistancenot Mode

Mode

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

Where each one falls short

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

Cube

  • Per-developer licensing can be expensive for large analytics teams
  • Additional cost for Explorer and Viewer roles beyond developers
  • Semantic layer approach requires upfront modeling investment
  • Smaller connector ecosystem than dedicated BI platforms
  • May be overengineered for simple reporting needs

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

Pricing, plan by plan

Cube

Free
  • FreeFree
    • For hobbyists and personal projects
    • Basic data source connection
    • Semantic modeling
  • Starter$40/developer/month
    • Extended agent limits
    • Premium LLMs
    • Unlimited workbooks
  • Premium$80/developer/month
    • All Starter features
    • Embedded dashboards
    • Embedded analytics chat
  • Enterprise$null/custom
    • 99.990% uptime SLA
    • Dedicated single-tenant installation
    • Bring Your Own Cloud

Mode

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

Which should you pick?

Choose Cube if

  • You need analytics chat.
  • You want to start without paying.
  • You work on Cloud, Self-hosted.
  • You also want workbooks.
Cube review

Choose Mode if

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

Questions people ask

Is Cube or Mode better?
Neither clearly leads. Cube starts at Free and Mode at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Cube or Mode?
Cube starts at Free and Mode at Free.
Does Cube or Mode run on more platforms?
Cube runs on Cloud, Self-hosted. Mode runs on Web.
Can I use Cube for free?
Both have a free tier, so you can try either at no cost before committing.
What is Cube best used for?
Cube is most often used for building governed semantic data models for analytics, embedding analytics into customer-facing products, enabling natural language data queries for teams, creating conversational dashboards with ai assistance. Of those, building governed semantic data models for analytics and embedding analytics into customer-facing products are not what Mode is typically brought in for.
What can Cube do that Mode cannot?
Cube covers Analytics Chat, Workbooks, Dashboards, Embedded Analytics. Mode covers SQL Editor, Python/R Notebooks, Interactive Reports, Version Control.

Answered from the vendors’ own pages

Cube: What is the cost per developer on Cube?

Starter plan costs $40/developer/month. Premium adds embedded analytics at $80/developer/month. Explorer and Viewer roles cost $40 and $20/month respectively.

Source
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
Cube: What uptime SLAs does Cube offer?

Premium plan offers 99.950% uptime SLA. Enterprise plan provides 99.990% uptime SLA with dedicated support.

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
Cube: Can I use Cube for free?

Yes, the Free plan includes basic data source connection, semantic modeling, workbooks, and dashboards for hobbyists and personal projects.

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
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