Matomo VS Apache Flink

Matomo Reviews

Apache Flink Reviews

Matomo mentions (82)

• 🔥Matomo 5 UPGRADE - A step-by-step GUIDE 🤌

  Matomo just released their major v5 upgrade with following key improvements:. - Source: dev.to / 4 months ago

• 11 Ways to Optimize Your Website

  There are many good, lightweight, and open-source alternatives to Google Analytics, such as Plausible, Matomo, Fathom, Simple Analytics, and so on. Many of these options are open-source, and can be self-hosted. - Source: dev.to / 6 months ago

• Mobile apps illegally share your personal data

  You can for example use analytics that aren't spyware, and hence don't even have to try to trick users giving "consent" to things they don't really want. Seriously: what share of people actually want their behavior to be tracked for ad companies to make more money? https://matomo.org/. - Source: Hacker News / 8 months ago

• Ask HN: Is Google Analytics that useful?

  Matomo is a GDPR-compliant and open-source analytics platform. You can either host it yourself or use Matomo’s hosted version. https://matomo.org/. - Source: Hacker News / 8 months ago

• Companies must stop using Google Analytics

  I tried the self-hosted version of Matomo [1][2] a few years back but I remember it was a bit underwhelming for the effort required to set it up. https://matomo.org. - Source: Hacker News / 10 months ago

Apache Flink mentions (27)

• Top 10 Common Data Engineers and Scientists Pain Points in 2024

  Data scientists often prefer Python for its simplicity and powerful libraries like Pandas or SciPy. However, many real-time data processing tools are Java-based. Take the example of Kafka, Flink, or Spark streaming. While these tools have their Python API/wrapper libraries, they introduce increased latency, and data scientists need to manage dependencies for both Python and JVM environments. For example,... - Source: dev.to / 27 days ago

• Choosing Between a Streaming Database and a Stream Processing Framework in Python

  Other stream processing engines (such as Flink and Spark Streaming) provide SQL interfaces too, but the key difference is a streaming database has its storage. Stream processing engines require a dedicated database to store input and output data. On the other hand, streaming databases utilize cloud-native storage to maintain materialized views and states, allowing data replication and independent storage scaling. - Source: dev.to / 3 months ago

• Go concurrency simplified. Part 4: Post office as a data pipeline

  Also, this knowledge applies to learning more about data engineering, as this field of software engineering relies heavily on the event-driven approach via tools like Spark, Flink, Kafka, etc. - Source: dev.to / 5 months ago

• Five Apache projects you probably didn't know about

  Apache SeaTunnel is a data integration platform that offers the three pillars of data pipelines: sources, transforms, and sinks. It offers an abstract API over three possible engines: the Zeta engine from SeaTunnel or a wrapper around Apache Spark or Apache Flink. Be careful, as each engine comes with its own set of features. - Source: dev.to / 5 months ago

• Getting Started with Flink SQL, Apache Iceberg and DynamoDB Catalog

  Due to the technology transformation we want to do recently, we started to investigate Apache Iceberg. In addition, the data processing engine we use in house is Apache Flink, so it's only fair to look for an experimental environment that integrates Flink and Iceberg. - Source: dev.to / 5 months ago