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Machine Learning · head to head

Databricks vs Heap

Databricks logo

Databricks

Machine Learning

Unified analytics platform for data engineering and data science

From
Free
Rated
-
Heap logo

Heap

Technology

Product analytics for the modern product team

From
Free
Rated
-

The short version

  • Each has a real cost: Databricks cloud compute is billed separately by the cloud provider on top of Databricks DBU charges; Heap no built-in A/B testing or feature flags; requires integration with separate tools for experimentation
  • They diverge on capability: Databricks covers Delta Lake, Heap covers Autocapture.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Databricks and Heap actually diverge.

Attributes where Databricks and Heap differ
AttributeDatabricksHeap
Pricing modelusage-basedUnknown
PlatformsWeb, Aws, Azure, GcpWeb, iOS, Android
CategoryMachine LearningTechnology

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), founded (2013).

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 Databricks

  • Delta Lake
  • Apache Spark
  • MLflow
  • Unity Catalog
  • Photon Engine
  • Collaborative Notebooks
  • Auto-scaling
  • AWS

Only in Heap

  • Autocapture
  • Retroactive analytics
  • Session replay
  • Funnel analysis
  • User segmentation
  • Path analysis
  • Data science
  • Virtual events

What people use each for

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

Databricks

  • Running Spark data engineering pipelines on managed clustersnot Heap
  • Building a lakehouse over data in cloud object storagenot Heap
  • Training and serving machine learning models alongside the datanot Heap

Heap

  • User behavior analysisnot Databricks
  • Conversion optimizationnot Databricks
  • Product adoptionnot Databricks
  • Customer journey mappingnot Databricks
  • A/B testing analysisnot Databricks

Where each one falls short

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

Databricks

  • Cloud compute is billed separately by the cloud provider on top of Databricks DBU charges
  • The free trial lasts 14 days
  • Discounts require a Committed Use Contract, with larger commitments needed for larger discounts
  • Azure Databricks pricing is set by Microsoft rather than by Databricks
  • Security and compliance capabilities are sold as separate platform add ons rather than included in the base rate

Heap

  • No built-in A/B testing or feature flags; requires integration with separate tools for experimentation
  • Group analytics and advanced features require a sales conversation, not self-serve
  • Cloud-only deployment; no self-hosted option for data security or compliance requirements
  • Session replay lacks developer debugging tools compared to PostHog
  • Pricing for Growth and Pro plans requires direct sales contact; no transparency on how pricing scales

Pricing, plan by plan

Databricks

Free
  • Community EditionFree
    • Limited cluster
    • Notebook environment
    • Community support
  • Standard$0.07/DBU
    • Jobs compute
    • SQL compute
    • Standard support

Heap

Free
  • FreeFree
    • Up to 10,000 monthly sessions
    • Basic charts
    • 6 months data history
  • Growth$undefined/custom
    • Custom session pricing
    • Sense AI assistant
    • 12 months data history
  • Pro$undefined/custom
    • Custom session pricing
    • Account analytics
    • Engagement matrix
  • Premier$undefined/custom
    • Custom session pricing
    • Data warehouse integration
    • Unlimited projects

Which should you pick?

Choose Databricks if

  • You need delta lake.
  • You want to start without paying.
  • You work on Web, Aws, Azure, Gcp.
  • You also want apache spark.

Choose Heap if

  • You need autocapture.
  • You want to start without paying.
  • You work on Web, iOS, Android.
  • You also want retroactive analytics.

Questions people ask

Is Databricks or Heap better?
Neither clearly leads. Databricks starts at Free and Heap at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Databricks or Heap?
Databricks starts at Free and Heap at Free.
Does Databricks or Heap run on more platforms?
Databricks runs on Web, Aws, Azure, Gcp. Heap runs on Web, iOS, Android.
Can I use Databricks for free?
Both have a free tier, so you can try either at no cost before committing.
What is Databricks best used for?
Databricks is most often used for running spark data engineering pipelines on managed clusters, building a lakehouse over data in cloud object storage, training and serving machine learning models alongside the data. Of those, running spark data engineering pipelines on managed clusters and building a lakehouse over data in cloud object storage are not what Heap is typically brought in for.
What can Databricks do that Heap cannot?
Databricks covers Delta Lake, Apache Spark, MLflow, Unity Catalog. Heap covers Autocapture, Retroactive analytics, Session replay, Funnel analysis.

Answered from the vendors’ own pages

Databricks: How is Databricks priced?

Databricks bills pay as you go with no up front cost, charging per second for the products used. Consumption is measured in Databricks Units, a normalised unit of processing power on the platform.

Source
Heap: What does Heap's autocapture feature do?

Heap's autocapture is a single code snippet that automatically captures every click, swipe, tap, pageview, and form fill on your website and apps without requiring manual event setup. Once installed, Heap captures the entire digital experience of every user on every platform with no ongoing engineering maintenance needed.

Source
Databricks: Does Databricks publish a per DBU price?

Not on its main pricing page. Rates vary by product and instance type, and Databricks directs buyers to individual product pricing pages and a calculator rather than listing a single figure.

Source
Heap: What are Heap's pricing plans and how much do they cost?

Heap offers a Free plan for up to 10,000 monthly sessions. Growth, Pro, and Premier plans use custom session-based pricing that requires contacting sales for a quote. Free includes basic charts and 6 months data history. Growth adds the Sense AI assistant. Pro adds account analytics. Premier adds data warehouse integration and dedicated customer success management.

Source
Databricks: Does the Databricks price include cloud costs?

No. Databricks states that if you configure it to work with your own cloud account, your cloud provider still charges you separately for the underlying resources.

Source
Heap: Does Heap include session replay and A/B testing?

Heap includes integrated session replay showing exactly what users did on your site. However, Heap does not include built-in A/B testing or feature flags. Teams requiring these capabilities must use separate tools or integrate with third-party platforms.

Source
Databricks: Can I get a discount on Databricks?

Databricks offers Committed Use Contracts, where larger usage commitments earn greater benefits, including options to use commitments flexibly across multiple clouds.

Source
Heap: What integrations does Heap support?

Heap supports over 100 integrations connecting to business tools including marketing platforms, CRMs, and data warehouses. This allows insights to reach relevant teams and ensures data flows to other business systems automatically.

Source
Heap: Does Heap offer self-hosting or is it cloud-only?

Heap is cloud-only and does not offer self-hosted options. Organizations requiring on-premises deployment should consider alternatives like PostHog which supports self-hosting alongside its cloud product.

Source
Heap: What is Sense and how does it help with analytics?

Sense Chat is Heap's AI assistant that enables users to access analytics without extensive technical knowledge. It allows teams to ask questions about user behavior and get answers directly without lengthy onboarding or technical expertise, making insights more accessible to non-technical stakeholders.

Source
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