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Business Intelligence · head to head

Cube vs Preset

Cube logo

Cube

Business Intelligence

AI-native analytics platform with semantic layer and governed access

From
Free
Rated
-
Full reviewWebsite
Preset logo

Preset

Business Intelligence

Managed Apache Superset

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Cube per-developer licensing can be expensive for large analytics teams; Preset limited SQL IDE advanced features compared to specialized query tools
  • They diverge on capability: Cube covers Analytics Chat, Preset covers Managed Superset.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Cube and Preset actually diverge.

Attributes where Cube and Preset differ
AttributeCubePreset
Pricing modelPer-developer seats with volume pricingUnknown
PlatformsCloud, Self-hostedWeb, Cloud
FoundedUnknown2019

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 Preset

  • Managed Superset
  • Auto-scaling
  • Enterprise Security
  • Custom Branding
  • API Access
  • Snowflake
  • BigQuery
  • Redshift

What people use each for

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

Cube

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

Preset

  • 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

Preset

  • Limited SQL IDE advanced features compared to specialized query tools
  • Viewer licenses add substantial cost for embedded analytics deployments
  • Dataset-centric approach requires preprocessing by data teams for some use cases

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

Preset

Free

No published plan breakdown. See the Preset review.

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 Preset if

  • You need managed superset.
  • You want to start without paying.
  • You work on Web, Cloud.
  • You also want auto-scaling.
Preset review

Questions people ask

Is Cube or Preset better?
Neither clearly leads. Cube starts at Free and Preset at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Cube or Preset?
Cube starts at Free and Preset at Free.
Does Cube or Preset run on more platforms?
Cube runs on Cloud, Self-hosted. Preset runs on Web, Cloud.
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 Preset is typically brought in for.
What can Cube do that Preset cannot?
Cube covers Analytics Chat, Workbooks, Dashboards, Embedded Analytics. Preset covers Managed Superset, Auto-scaling, Enterprise Security, Custom Branding.

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
Preset: Is Preset free?

Preset offers a free tier for small teams called Starter with 5 users and no credit card required. Paid plans start at $25 per user per month.

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
Preset: Can I export my data from Preset?

Yes. Preset uses Apache Superset and the founders contribute over 75% of commits to the open-source project, enabling migration to Superset without vendor lock-in.

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
Preset: Does Preset include embedded analytics?

Yes. Embedded dashboards are available on Professional and Enterprise plans, with viewer licenses starting at $500 per month for 50 licenses.

Source
Preset: What is the enterprise pricing for Preset?

Enterprise plans are custom quoted. The median buyer pays $35,495 per year.

Source
Preset: Does Preset support AI-powered analytics?

Yes. As of 2026, Preset includes an AI Chatbot and MCP (Model Context Protocol) integration for building charts and dashboards via natural language.

Source
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