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Matomo VS Apache Kafka

Compare Matomo VS Apache Kafka and see what are their differences

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  3. » Reviews
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Matomo logo Matomo

Matomo is an open-source web analytics platform

Apache Kafka logo Apache Kafka

Apache Kafka is an open-source message broker project developed by the Apache Software Foundation written in Scala.
  • Matomo Landing page
    Landing page //
    2023-10-23
  • Apache Kafka Landing page
    Landing page //
    2022-10-01

Matomo features and specs

  • Open Source
    Matomo is an open-source platform, allowing for customization and transparency in how data is collected and processed.
  • Data Ownership
    Users have full ownership of their data, ensuring that no third-party entities have access to sensitive information.
  • Privacy Compliance
    Matomo is designed with privacy in mind, making it easier to comply with GDPR, CCPA, and other data protection regulations.
  • Self-Hosting Option
    Matomo can be self-hosted, giving users complete control over their data security and server environment.
  • Feature-Rich
    The platform offers a wide range of features, including A/B testing, heatmaps, session recording, and more.
  • Community Support
    A large community of users and developers contributes plugins, improvements, and support, enriching the ecosystem.

Possible disadvantages of Matomo

  • Complex Setup
    The initial setup, especially for self-hosted versions, can be complex and time-consuming, requiring technical expertise.
  • Resource Intensive
    Running Matomo, particularly its self-hosted version, can be resource-intensive, requiring significant server capabilities.
  • Cost for Advanced Features
    While the basic version is free, advanced features and cloud hosting come at a cost, which might be expensive for small businesses.
  • Limited Integrations
    Matomo offers fewer integrations with other marketing and analytics tools compared to some other platforms like Google Analytics.
  • Learning Curve
    New users may find the interface and advanced features challenging to learn and navigate initially.
  • Performance Issues
    Some users report performance issues, particularly with large volumes of data or on less powerful servers.

Apache Kafka features and specs

  • High Throughput
    Kafka is capable of handling thousands of messages per second due to its distributed architecture, making it suitable for applications that require high throughput.
  • Scalability
    Kafka can easily scale horizontally by adding more brokers to a cluster, making it highly scalable to serve increased loads.
  • Fault Tolerance
    Kafka has built-in replication, ensuring that data is replicated across multiple brokers, providing fault tolerance and high availability.
  • Durability
    Kafka ensures data durability by writing data to disk, which can be replicated to other nodes, ensuring data is not lost even if a broker fails.
  • Real-time Processing
    Kafka supports real-time data streaming, enabling applications to process and react to data as it arrives.
  • Decoupling of Systems
    Kafka acts as a buffer and decouples the production and consumption of messages, allowing independent scaling and management of producers and consumers.
  • Wide Ecosystem
    The Kafka ecosystem includes various tools and connectors such as Kafka Streams, Kafka Connect, and KSQL, which enrich the functionality of Kafka.
  • Strong Community Support
    Kafka has strong community support and extensive documentation, making it easier for developers to find help and resources.

Possible disadvantages of Apache Kafka

  • Complex Setup and Management
    Kafka's distributed nature can make initial setup and ongoing management complex, requiring expert knowledge and significant administrative effort.
  • Operational Overhead
    Running Kafka clusters involves additional operational overhead, including hardware provisioning, monitoring, tuning, and scaling.
  • Latency Sensitivity
    Despite its high throughput, Kafka may experience increased latency in certain scenarios, especially when configured for high durability and consistency.
  • Learning Curve
    The concepts and architecture of Kafka can be difficult for new users to grasp, leading to a steep learning curve.
  • Hardware Intensive
    Kafka's performance characteristics often require dedicated and powerful hardware, which can be costly to procure and maintain.
  • Dependency Management
    Managing Kafka's dependencies and ensuring compatibility between versions of Kafka, Zookeeper, and other ecosystem tools can be challenging.
  • Limited Support for Small Messages
    Kafka is optimized for large throughput and can be inefficient for applications that require handling a lot of small messages, where overhead can become significant.
  • Operational Complexity for Small Teams
    Smaller teams might find the operational complexity and maintenance burden of Kafka difficult to manage without a dedicated operations or DevOps team.

Matomo videos

+ Add

Matomo Analytics - Dashboards

More videos:

  • Review - WP-Matomo (WP-Piwik) Review: Open Source Analytics For WordPress
  • Review - AMU WEBD122 - Spohnholtz Piwik Analytics Review
  • Review - What are the differences between Matomo Analytics and Google Analytics
  • Review - Matomo On-Premise installation overview

Apache Kafka videos

+ Add

Apache Kafka Tutorial | What is Apache Kafka? | Kafka Tutorial for Beginners | Edureka

More videos:

  • Review - Apache Kafka - Getting Started - Kafka Multi-node Cluster - Review Properties
  • Review - 4. Apache Kafka Fundamentals | Confluent Fundamentals for Apache Kafka®
  • Review - Apache Kafka in 6 minutes
  • Review - Apache Kafka Explained (Comprehensive Overview)
  • Review - 2. Motivations and Customer Use Cases | Apache Kafka Fundamentals

Category Popularity

0-100% (relative to Matomo and Apache Kafka)

Matomo

Apache Kafka

Analytics
100 100%
Analytics
0% 0
Stream Processing
0 0%
Stream Processing
100% 100
Web Analytics
100 100%
Web Analytics
0% 0
Data Integration
0 0%
Data Integration
100% 100

User comments

Share your experience with using Matomo and Apache Kafka. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Matomo and Apache Kafka

Matomo Reviews

Top 5 Plausible Analytics Alternatives in 2024
With advanced web analytics Matomo Analytics also provides eCommerce analytics capabilities.
Source: www.putler.com
Top 9 Plausible Analytics alternatives in 2024
Matomo, one of the best Plausible analytics alternatives, an open-source analytics platform, prioritizes data ownership and customization. It allows users to host analytics on their servers, ensuring complete control over collected data.
Source: usermaven.com
Top 5 Self-Hosted, Open Source Alternatives to Google Analytics
Use Case Example: A healthcare website uses Matomo to securely track user interactions while maintaining strict compliance with health data privacy regulations.
Source: zeabur.com
Unleashing Alternatives: 15 Advanced Tools for Web Analytics Just Like Google Analytics(Brief and Crisp)
Piwik PRO offers similar if not same benefits as mentioned above and makret themselves a tool for “Technical Marketers”. If you did not know then let me tell you that Matomo and Piwik PRO both these products emerged from the humble beginnings of the Piwik project but have since charted a slightly different paths.
Source: rishikap372.medium.com
Unleashing Alternatives: 15 Advanced Tools for Web Analytics Just Like Google Analytics(Brief and Crisp)
Piwik PRO offers similar if not same benefits as mentioned above and makret themselves a tool for “Technical Marketers”. If you did not know then let me tell you that Matomo and Piwik PRO both these products emerged from the humble beginnings of the Piwik project but have since charted a slightly different paths.
Source: medium.com

Apache Kafka Reviews

Best ETL Tools: A Curated List
Debezium is an open-source Change Data Capture (CDC) tool that originated from RedHat. It leverages Apache Kafka and Kafka Connect to enable real-time data replication from databases. Debezium was partly inspired by Martin Kleppmann’s "Turning the Database Inside Out" concept, which emphasized the power of the CDC for modern data pipelines.
Source: estuary.dev
Best message queue for cloud-native apps
If you take the time to sort out the history of message queues, you will find a very interesting phenomenon. Most of the currently popular message queues were born around 2010. For example, Apache Kafka was born at LinkedIn in 2010, Derek Collison developed Nats in 2010, and Apache Pulsar was born at Yahoo in 2012. What is the reason for this?
Source: docs.vanus.ai
Are Free, Open-Source Message Queues Right For You?
Apache Kafka is a highly scalable and robust messaging queue system designed by LinkedIn and donated to the Apache Software Foundation. It's ideal for real-time data streaming and processing, providing high throughput for publishing and subscribing to records or messages. Kafka is typically used in scenarios that require real-time analytics and monitoring, IoT applications,...
Source: blog.iron.io
10 Best Open Source ETL Tools for Data Integration
It is difficult to anticipate the exact demand for open-source tools in 2023 because it depends on various factors and emerging trends. However, open-source solutions such as Kubernetes for container orchestration, TensorFlow for machine learning, Apache Kafka for real-time data streaming, and Prometheus for monitoring and observability are expected to grow in prominence in...
Source: testsigma.com
11 Best FREE Open-Source ETL Tools in 2024
Apache Kafka is an Open-Source Data Streaming Tool written in Scala and Java. It publishes and subscribes to a stream of records in a fault-tolerant manner and provides a unified, high-throughput, and low-latency platform to manage data.
Source: hevodata.com

Social recommendations and mentions

Based on our record, Apache Kafka should be more popular than Matomo. It has been mentiond 142 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Matomo mentions (85)

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Apache Kafka mentions (142)

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What are some alternatives?

When comparing Matomo and Apache Kafka, you can also consider the following products

Google Analytics - Improve your website to increase conversions, improve the user experience, and make more money using Google Analytics. Measure, understand and quantify engagement on your site with customized and in-depth reports.

RabbitMQ - RabbitMQ is an open source message broker software.

Plausible.io - Plausible Analytics is a simple, open-source, lightweight (< 1 KB) and privacy-friendly web analytics alternative to Google Analytics. Made and hosted in the EU, powered by European-owned cloud infrastructure 🇪🇺

Apache ActiveMQ - Apache ActiveMQ is an open source messaging and integration patterns server.

Fathom Analytics - Simple, trustworthy website analytics (finally)

StatCounter - StatCounter is a simple but powerful real-time web analytics service that helps you track, analyse and understand your visitors so you can make good decisions to become more successful online.

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