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Countly vs Rakam

Professional comparison and analysis to help you choose the right software solution for your needs.

Countly icon
Countly
Rakam icon
Rakam

Countly vs Rakam: The Verdict

Last updated: May 2026 · Comparison by Sugggest Editorial Team

Feature Countly Rakam
Sugggest Score
Category Business & Commerce Ai Tools & Services
Pricing Open Source Open Source

Product Overview

Countly
Countly

Description: Countly is an open source web analytics platform that provides insights into user behavior on mobile and web applications. It tracks sessions, page views, crashes, and more to help developers understand user engagement.

Type: software

Pricing: Open Source

Rakam
Rakam

Description: Rakam is an open-source analytics platform designed for large-scale data collection and analysis. It is optimized for scalability and high performance to support collecting and processing billions of events per day.

Type: software

Pricing: Open Source

Key Features Comparison

Countly
Countly Features
  • Real-time analytics dashboard
  • Crash reporting and analytics
  • User profiles and segmentation
  • Push and in-app messaging
  • A/B testing
  • Attribution analytics
  • Custom data collection via SDK
  • Data export and APIs
  • Mobile and web app analytics
Rakam
Rakam Features
  • Real-time data collection and processing
  • Scalable architecture
  • Support for large volumes of data
  • Customizable data pipelines
  • Query engine for ad-hoc analysis
  • Visualization and dashboarding
  • Alerting and anomaly detection

Pros & Cons Analysis

Countly
Countly
Pros
  • Open source and self-hosted
  • Detailed usage analytics
  • Flexible segmentation
  • Scales to large data volumes
  • Supports web and mobile apps
  • Active open source community
Cons
  • Requires technical expertise to install/configure
  • Limited pre-built integrations
  • Less out-of-box features than paid solutions
  • Lacks predictive analytics capabilities
  • UI not as polished as some competitors
Rakam
Rakam
Pros
  • Highly scalable and performant
  • Open source and free to use
  • Flexible and customizable
  • Real-time analytics capabilities
  • Designed for big data workloads
Cons
  • Limited out-of-the-box visualizations
  • Steep learning curve
  • Requires DevOps skills for setup and management
  • Not as feature rich as commercial alternatives

Pricing Comparison

Countly
Countly
  • Open Source
Rakam
Rakam
  • Open Source

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