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Apache Beam vs Kissflow: What are the differences?
Apache Beam: A unified programming model. It implements batch and streaming data processing jobs that run on any execution engine. It executes pipelines on multiple execution environments; Kissflow: Best Workflow Software. It is a workflow tool & business process workflow management software to automate your workflow process.
Apache Beam and Kissflow belong to "Workflow Manager" category of the tech stack.
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Pros of Apache Beam
- Open-source5
- Cross-platform5
- Portable2
- Unified batch and stream processing2
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What is Apache Beam?
It implements batch and streaming data processing jobs that run on any execution engine. It executes pipelines on multiple execution environments.
What is Kissflow?
It is a workflow tool & business process workflow management software to automate your workflow process.
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Jobs that mention Apache Beam and Kissflow as a desired skillset
What companies use Apache Beam?
What companies use Kissflow?
What companies use Kissflow?
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What tools integrate with Apache Beam?
What tools integrate with Kissflow?
What tools integrate with Apache Beam?
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What are some alternatives to Apache Beam and Kissflow?
Apache Spark
Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
Kafka Streams
It is a client library for building applications and microservices, where the input and output data are stored in Kafka clusters. It combines the simplicity of writing and deploying standard Java and Scala applications on the client side with the benefits of Kafka's server-side cluster technology.
Kafka
Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
Airflow
Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command lines utilities makes performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress and troubleshoot issues when needed.
Google Cloud Dataflow
Google Cloud Dataflow is a unified programming model and a managed service for developing and executing a wide range of data processing patterns including ETL, batch computation, and continuous computation. Cloud Dataflow frees you from operational tasks like resource management and performance optimization.