Gearpump
Apache Flink
Apache Spark
Spark Mail
Upsolver
Apache Kafka
Apache Storm
IQLECT
Kafka Streams
Apache Flink
Apache NiFi
Apache Airflow
KSQL
Apache Kafka
Faust
Apache Storm
Gearpump Kafka StreamsNo Gearpump videos yet. You could help us improve this page by suggesting one.
Based on our record, Kafka Streams seems to be a lot more popular than Gearpump. While we know about 14 links to Kafka Streams, we've tracked only 1 mention of Gearpump. 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.
You forgot gearpump http://incubator.apache.org/projects/gearpump.html. - 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 / 21 days 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 / about 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 / about 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 Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
Apache NiFi - An easy to use, powerful, and reliable system to process and distribute data.
Spark Mail - Spark helps you take your inbox under control. Instantly see what’s important and quickly clean up the rest. Spark for Teams allows you to create, discuss, and share email with your colleagues
Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.
Upsolver - Upsolver is a robust Data Lake Platform that simplifies big & streaming data integration, management and preparation on premise (HDFS) or in the cloud (AWS, Azure, GCP).
