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Business Intelligence · head to head

Pigment vs Sisense

Pigment logo

Pigment

Business Intelligence

Enterprise business planning platform for finance, sales and workforce modelling

From
On request
Rated
-
Full reviewWebsite
Sisense logo

Sisense

Business Intelligence

Infuse analytics everywhere

From
$10000/year
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Pigment no pricing is published and the structure has three moving parts, platform fee, use-case fees and tiered seats, so two companies of the same size can pay very different amounts and neither can benchmark the other.; Sisense pricing lacks transparency with opaque scaling costs and hidden fees for onboarding and training
  • They diverge on capability: Pigment covers Dimensional modelling, Sisense covers Embedded Analytics.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Pigment and Sisense actually diverge.

Attributes where Pigment and Sisense differ
AttributePigmentSisense
Starting priceOn request$10000/year
Pricing modelquoteUnknown
PlatformsWebWeb, Cloud, On-premises
FoundedUnknown2004

Identical on both: free tier (No), 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 Pigment

  • Dimensional modelling
  • Scenario planning
  • Data connectors
  • Application blocks
  • Reporting and boards
  • Access control
  • Audit trail
  • AI assistance

Only in Sisense

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

What people use each for

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

Pigment

  • A finance team retiring a fragile Excel consolidation that no one can audit and only one person can runnot Sisense
  • Sales operations modelling quota, territory and headcount capacity against a revenue plan in the same system finance usesnot Sisense
  • A company that needs monthly re-forecasting fast enough to run scenarios live in the leadership meetingnot Sisense
  • Replacing an ageing Anaplan estate where the model has become unmaintainable and per-workspace costs have crept upnot Sisense

Sisense

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

Where each one falls short

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

Pigment

  • No pricing is published and the structure has three moving parts, platform fee, use-case fees and tiered seats, so two companies of the same size can pay very different amounts and neither can benchmark the other.
  • Cost scales with planning processes rather than with company size, so a successful first deployment creates internal demand that directly increases the bill at renewal.
  • It requires a modelling owner. Without a person who understands dimensional design, teams rebuild spreadsheet patterns in Pigment and inherit all the maintenance problems they were trying to escape.
  • Implementation is partner-led and measured in months, so the payback horizon is long compared with lighter FP&A tools that a controller can configure alone.
  • The connector library covers major systems well but the long tail is thinner than the incumbents, and industry-specific source systems often need a warehouse or a file drop in between.

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

Pigment

On request
  • Pigment platform$undefined/year
    • Platform fee plus per use-case fees
    • Licences tiered as editor, contributor and explorer
    • No free tier and no self-service signup

Sisense

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

Which should you pick?

Choose Pigment if

  • You need dimensional modelling.
  • You also want scenario planning.
Pigment 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 Pigment or Sisense better?
Neither clearly leads. Pigment starts at On request and Sisense at $10000/year, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Pigment or Sisense?
Pigment starts at On request and Sisense at $10000/year.
Does Pigment or Sisense run on more platforms?
Pigment runs on Web. Sisense runs on Web, Cloud, On-premises.
What is Pigment best used for?
Pigment is most often used for a finance team retiring a fragile excel consolidation that no one can audit and only one person can run, sales operations modelling quota, territory and headcount capacity against a revenue plan in the same system finance uses, a company that needs monthly re-forecasting fast enough to run scenarios live in the leadership meeting, replacing an ageing anaplan estate where the model has become unmaintainable and per-workspace costs have crept up. Of those, a finance team retiring a fragile excel consolidation that no one can audit and only one person can run and sales operations modelling quota, territory and headcount capacity against a revenue plan in the same system finance uses are not what Sisense is typically brought in for.
What can Pigment do that Sisense cannot?
Pigment covers Dimensional modelling, Scenario planning, Data connectors, Application blocks. Sisense covers Embedded Analytics, AI/ML Integration, In-chip Technology, White-labeling.

Answered from the vendors’ own pages

Pigment: Does Pigment publish prices?

No. Expect a quote combining a platform fee, fees per planning use case, and seat licences split into editor, contributor and explorer tiers.

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
Pigment: Is Pigment an alternative to Anaplan?

It is positioned directly against Anaplan and much of its customer base is migrating from it, mainly citing modelling readability and recalculation speed.

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
Pigment: Can we use it without consultants?

In practice most deployments use Pigment or a partner for the initial build. Ongoing model changes can be handled in-house once someone owns the modelling discipline.

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
Pigment: Where is data hosted?

Pigment is a European vendor with regional hosting options, which is often the deciding factor for EU buyers with data residency requirements.

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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