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Spreadsheet & Data · head to head

Apache Superset vs Sisense

Apache Superset logo

Apache Superset

Spreadsheet & Data

Modern data exploration and visualization platform

From
Free
Rated
-
Full reviewWebsite
Sisense logo

Sisense

Business Intelligence

Infuse analytics everywhere

From
$10000/year
Rated
-
Full reviewWebsite

The short version

  • Only Apache Superset has a free tier, so it costs nothing to try first.
  • Each has a real cost: Apache Superset distributed under Apache License 2.0 with no official vendor-hosted SaaS; deploying it requires self-managed infrastructure since the Apache Software Foundation does not sell a managed offering.; Sisense pricing lacks transparency with opaque scaling costs and hidden fees for onboarding and training
  • They diverge on capability: Apache Superset covers 40+ Visualizations, Sisense covers Embedded Analytics.

Where they differ

Only the attributes on which Apache Superset and Sisense actually diverge.

Attributes where Apache Superset and Sisense differ
AttributeApache SupersetSisense
Starting priceFree$10000/year
Pricing modelopen-sourceUnknown
Free tierYesNo
PlatformsWeb, Self-hosted, DockerWeb, Cloud, On-premises
CategorySpreadsheet & DataBusiness Intelligence
Founded19992004

Identical on both: 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 Apache Superset

  • 40+ Visualizations
  • SQL IDE
  • Semantic Layer
  • Caching
  • Security
  • PostgreSQL
  • MySQL
  • Presto

Only in Sisense

  • Embedded Analytics
  • AI/ML Integration
  • In-chip Technology
  • White-labeling
  • REST API
  • AWS
  • Azure
  • Google Cloud

Both cover

  • Snowflake
  • Web support

What people use each for

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

Apache Superset

  • Self-service analytics
  • Data exploration
  • Ad-hoc reporting
  • Collaborative analysis
  • Embedded analytics

Sisense

  • Self-service analytics
  • Data exploration
  • Ad-hoc reporting
  • Collaborative analysis
  • Embedded analytics

Both are used for self-service analytics, data exploration, ad-hoc reporting, collaborative analysis, embedded analytics, on those jobs the choice comes down to price and fit rather than capability.

Where each one falls short

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

Apache Superset

  • Distributed under Apache License 2.0 with no official vendor-hosted SaaS; deploying it requires self-managed infrastructure since the Apache Software Foundation does not sell a managed offering.

Sisense

  • Pricing lacks transparency with opaque scaling costs and hidden fees for onboarding and training
  • Limited connector ecosystem compared to competitors; missing native connectors to many data sources
  • Dashboard customization options are limited; widgets cannot span multiple rows, restricting layout possibilities
  • Performance issues reported with large datasets and stability problems with data cubes

Pricing, plan by plan

Apache Superset

Free
  • Open SourceFree
    • Full Features
    • Self-hosted
    • Community Support

Sisense

$10000/year
  • Small Team$10000/year minimum
    • Basic analytics dashboards
    • Limited data sources
  • Mid-Market$null/custom
    • Advanced analytics
    • Multiple data sources
    • Custom integrations
  • Enterprise$60000/year+
    • Advanced AI analytics
    • Premium support
    • Custom development

Which should you pick?

Choose Apache Superset if

  • You need 40+ visualizations.
  • You want to start without paying.
  • You work on Web, Self-hosted, Docker.
  • You also want sql ide.
Apache Superset review

Choose Sisense if

  • You need embedded analytics.
  • You work on Web, Cloud, On-premises.
  • You also want ai/ml integration.
Sisense review

Questions people ask

Is Apache Superset or Sisense better?
Neither clearly leads. Apache Superset starts at Free and Sisense at $10000/year, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Apache Superset or Sisense?
Apache Superset has a free tier; the other does not. Paid plans start at Free for Apache Superset and $10000/year for Sisense.
Does Apache Superset or Sisense run on more platforms?
Apache Superset runs on Web, Self-hosted, Docker. Sisense runs on Web, Cloud, On-premises.
Can I use Apache Superset for free?
Yes. Apache Superset has a free tier, so you can try it without paying. Sisense starts at $10000/year.
What is Apache Superset best used for?
Apache Superset is most often used for self-service analytics, data exploration, ad-hoc reporting, collaborative analysis.
What can Apache Superset do that Sisense cannot?
Apache Superset covers 40+ Visualizations, SQL IDE, Semantic Layer, Caching. Sisense covers Embedded Analytics, AI/ML Integration, In-chip Technology, White-labeling. Both handle Snowflake, Web support.

Answered from the vendors’ own pages

Sisense: What is Sisense primarily used for?

Sisense is an embedded analytics platform that combines data ingestion, modeling, and dashboarding, allowing organizations to embed analytics and insights directly into their applications and workflows.

Source
Sisense: Does Sisense have a transparent pricing model?

Sisense pricing is not publicly listed and requires contacting sales. Typical costs start at $10,000 per year for small teams but can scale to $60,000+ annually depending on users, data volume, number of data sources, and complexity. AI capabilities typically add 20-30% to base costs.

Source
Sisense: What data sources can Sisense connect to?

Sisense provides pre-built connectors for popular applications including Salesforce, Google Analytics, Zendesk, and others. It also supports custom connections through APIs and SDKs for specialized data sources.

Source
Sisense: Is Sisense easy to use for non-technical users?

Sisense requires significant technical expertise to set up, particularly for creating Elasticubes (database caches) which often need SQL code. While it promotes codeless reporting, typical implementations require a technical resource.

Source
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Related pages

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