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Based on our record, Hadoop seems to be more popular. It has been mentiond 15 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.
Did you check out tools like https://hadoop.apache.org/ ? Source: about 1 year ago
There are different ways to implement parallel dataflows, such as using parallel data processing frameworks like Apache Hadoop, Apache Spark, and Apache Flink, or using cloud-based services like Amazon EMR and Google Cloud Dataflow. It is also possible to use parallel dataflow frameworks to handle big data and distributed computing, like Apache Nifi and Apache Kafka. Source: about 1 year ago
There are several frameworks available for batch processing, such as Hadoop, Apache Storm, and DataTorrent RTS. - Source: dev.to / over 1 year ago
A copy of Hadoop installed on each of these machines. You can download Hadoop from the Apache website, or you can use a distribution like Cloudera or Hortonworks. - Source: dev.to / over 1 year ago
The Apache™ Hadoop™ project develops open-source software for reliable, scalable, distributed computing. - Source: dev.to / over 1 year ago
Mover - Mover is a platform for moving files, streamlines the process of transferring users' data to the cloud.
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
Data2CRM.Migration - Unique automated CRM migration service that allows you to perform flawless data migration between various CRM platforms.
Apache Cassandra - The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance.
Import2 - Import2 is an online data import service that helps you transfer business or personal data between cloud apps.
Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.