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NetSpring vs. Kubit

Both NetSpring and Kubit offer a warehouse-native platform for product analytics that avoids the data silos and inconsistencies of first-generation tools like Amplitude and Mixpanel.

However with NetSpring QueryDirect, there is absolutely no data duplication while achieving performance at scale. You have full transparency into compute and the exact SQL used to query the warehouse. This also means you can take full advantage of the credits you’ve negotiated with your data warehouse provider!

NetSpring also does not restrict you to a user-event paradigm. Its flexible data model uniquely enables Product and Data teams to calculate any metric or custom attribute and service both product analytics use cases and ad hoc visual data exploration, all from a single self-service platform.

NetSpring
Kubit
Core Templates
Fully supported
Fully supported
Self-serve common reports for event segmentation, funnel, path, retention, impact, etc.
Ad Hoc Visual Exploration
Fully supported
Not supported
Create flexible visualizations from any combination of events, metrics, and dimensions available from the warehouse through a freeform drag and drop interface
Custom Metrics
Fully supported
Not supported
Express analytic computations of arbitrary complexity to define business-impactful metrics – all from a UI-driven interface.
Dashboards
Fully supported
Fully supported
Get a full picture of product performance and how customer behavior impacts key business metrics
Cohort Analysis
Fully supported
Fully supported
Group users based on common usage patterns, events, and attributes
Multi-Actor Analysis
Fully supported
Not supported
Analyze events across any actor, such as projects, tasks, tickets, or documents – not just users
Events Data Warehouse Connection
Fully supported
Fully supported
Point to event streams in your data warehouse, like basic user-event tables
Flexible Data Model
Fully supported
Not supported
Natively leverage all data in the warehouse to calculate any metric or custom attribute, without writing any SQL
Transparent Query Generation
Fully supported
Not supported
See the exact SQL used to query the warehouse – no black boxes
Mutable Data
Fully supported
Limited capabilities
Reflect changes to underlying records in the warehouse automatically in any existing analysis
No Data Duplication
Fully supported
Limited capabilities
No copies of the data are required
Data Governance
Fully supported
Fully supported
Leverage existing governance and data quality checks upstream of analytics tables in the warehouse
Security & Compliance
Fully supported
Limited capabilities
Prevent sensitive data from leaving your secure enterprise environment
Transparent Pricing
Fully supported
Not supported
Have full transparency into compute costs
Cost vs. Performance
Fully supported
Not supported
Control the trade-offs between cost and performance based on your business needs at any given time

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Additional Resources

Buyers Guide for Warehouse-Native Product Analytics

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Ergatta Leverages Behavioral Analytics to Shape Fitness Habits of Users

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Bonfire case study

Bonfire Increases Activation Rates 80% with Behavioral Cohort Analysis

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