Apache NiFi might be a bit more popular than Kafka Streams. We know about 16 links to it since March 2021 and only 14 links to Kafka Streams. 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.
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 1 month ago
We’re not discussing the technical details behind the deduplication process. It could be Apache Flink, Apache Spark, or Kafka Streams. Anyway, it’s out of the scope of this article. - Source: dev.to / over 1 year ago
In pub-sub systems, you cannot have multiple services to consume the same data because the messages are deleted after being consumed by one consumer. Whereas in Kafka, you can have multiple services to consume. This opens the door to a lot of opportunities such as Kafka streams, Kafka connect. We’ll discuss these at the end of the series. - Source: dev.to / over 1 year ago
Internally, Streamiz use the .Net client for Apache Kafka released by Confluent and try to provide the same features than Kafka Streams. There is gap between these two library, but the trend is decreasing after each release. - Source: dev.to / over 1 year ago
Both Kafka and Pulsar provide some kind of stream processing capability, but Kafka is much further along in that regard. Pulsar stream processing relies on the Pulsar Functions interface which is only suited for simple callbacks. On the other hand, Kafka Streams and ksqlDB are more complete solutions that could be considered replacements for Apache Spark or Apache Flink, state-of-the-art stream-processing... - Source: dev.to / over 1 year ago
Apache NIFI (https://nifi.apache.org/). It uses the concept of Flow-based programming. Also its so underacknolged but this tool is very flexible. I have used as an Event Bus all the 3rd-Party Integrations. - Source: Hacker News / 8 months ago
Presently setting up Apache Nifi + Apache MiNiFi for the ETL portion of my work. NiFi was easy enough to figure out; but the docs for MiNiFi have been a pain due to differences between the Java and C++ versions. I then entirely configured it with the Java version so that it was easier to search for answers for the MiNiFi yaml syntax. Source: 11 months ago
NIFI, like most Apache projects does most of its discussion on its mailing lists, but also has a slack. Source: about 1 year ago
You might want to give a tool like nifi a try: Https://nifi.apache.org/. Source: about 1 year ago
Recently I got a job at a new company and now I need to learn about Clickhouse, Docker, Apache Nifi and Kafka. I've found the decks about Docker and Kafka, but I can't find ones about Clickhouse and Nifi. Https://clickhouse.com/docs/en/intro Https://nifi.apache.org/. Source: about 1 year ago
Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
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.
Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.
Histats - Start tracking your visitors in 1 minute!
KSQL - Confluent KSQL is the streaming SQL engine that enables real-time data processing against Apache Kafka®.
AFSAnalytics - AFSAnalytics.