Opa VS Apache Flink

I remember Opa http://opalang.org/ tried something similar at the time when MongoDB was new and modern. - Source: Hacker News / 8 months ago

We come across some web frameworks and technologies that we think will succeed, but they wither away as time passes by and don't succeed to the level we expected. Which web frameworks and or technologies did you come across that you thought would succeed but did not as per your expectations? For example, I thought that Opa Lang[0] and UrWeb[1] would succeed but did not, even though the ideas were sound. [0]... - Source: Hacker News / 9 months ago

I think the Opa language was doing JSX-like code in the frontend before JSX http://opalang.org/ Both Opa and JSX were created in 2011. Opa had other innovations as well, such having the same code base run on both client and server (like Next.js). Unfortunately it didn't get traction and was abandoned by the creators. - Source: Hacker News / almost 3 years 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 / 25 days 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 / 3 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

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

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