Countly is a product analytics solution and innovation enabler that helps organizations track product performance and user journey and behavior across mobile, web, and desktop applications. Ensuring privacy by design, it allows organizations to innovate and enhance their products to provide personalized and customized customer experiences, and meet key business and revenue goals.
Track, measure, and take action - all without leaving Countly.
Based on our record, Apache Flink should be more popular than Countly. It has been mentiond 29 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.
I’ve recently started my journey with Apache Flink. As I learn certain concepts, I’d like to share them. One such "learning" is the expansion of array type columns in Flink SQL. Having used ksqlDB in a previous life, I was looking for functionality similar to the EXPLODE function to "flatten" a collection type column into a row per element of the collection. Because Flink SQL is ANSI compliant, it’s no surprise... - Source: dev.to / 7 days ago
You should let the Apache Flink team know, they mention exactly-once processing on their home page (under "correctness guarantees") and in their list of features. [0] https://flink.apache.org/ [1] https://flink.apache.org/what-is-flink/flink-applications/#building-blocks-for-streaming-applications. - Source: Hacker News / 21 days ago
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 / about 2 months ago
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 / 4 months ago
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
Hello HN, founder of Countly (https://count.ly) here. As you might know, we are the creators of one of the first open-source product analytics platforms that has 10+ SDKs for mobile, desktop and web applications. We've been working on a new SaaS, myCountly, to help you launch your own Countly servers in any location, so your user data stays close to home. We are going to do an alpha launch soon, and looking for... - Source: Hacker News / over 1 year ago
Is countly still operational? Can't connect to their website https://count.ly/. Source: over 1 year ago
Always surprised more people don’t use countly. Runs nice in docker or digital ocean. https://count.ly. Been self hosting it for years with few issues. - Source: Hacker News / over 2 years ago
Countly (website, GitHub) is also an open-source product analytics platform that is designed primarily for marketing organizations. It helps marketers track website information (website transactions, campaigns, and sources that led visitors to the website, etc.). Countly also collects real-time mobile analytics metrics like active users, time spent in-app, customer location, etc., in a unified view on your dashboard. - Source: dev.to / over 2 years ago
Self-hosted alternatives to Google Analytics include: Matomo, open core with a broad feature set: https://matomo.org Countly, open core with desktop and mobile tracking: https://count.ly/ Plausible, open source with a simple feature set: https://plausible.io. - Source: Hacker News / about 3 years ago
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