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Kylo VS Amazon EMR

Compare Kylo VS Amazon EMR and see what are their differences

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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Kylo logo Kylo

Kylo is an end-to-end data lake management software that provides data from many sources in an automated fashion and optimizes it.

Amazon EMR logo Amazon EMR

Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.
  • Kylo Landing page
    Landing page //
    2022-02-17
  • Amazon EMR Landing page
    Landing page //
    2023-04-02

Kylo videos

+ Add

The Last Jedi Movie Review - KYLO REN REACTS

More videos:

  • Review - Kylo Ren Reviews Rogue One: A Star Wars Story (SPOILERS!)
  • Review - KYLO REN REVIEWS SOLO: A Star Wars Story

Amazon EMR videos

+ Add

Amazon EMR Masterclass

More videos:

  • Review - Deep Dive into What’s New in Amazon EMR - AWS Online Tech Talks
  • Tutorial - How to use Apache Hive and DynamoDB using Amazon EMR

Category Popularity

0-100% (relative to Kylo and Amazon EMR)

Kylo

Amazon EMR

Business & Commerce
100 100%
Business & Commerce
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100
Online Services
100 100%
Online Services
0% 0
Big Data
0 0%
Big Data
100% 100

User comments

Share your experience with using Kylo and Amazon EMR. For example, how are they different and which one is better?
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Social recommendations and mentions

Based on our record, Amazon EMR seems to be more popular. It has been mentiond 10 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.

Kylo mentions (0)

We have not tracked any mentions of Kylo yet. Tracking of Kylo recommendations started around Feb 2022.

Amazon EMR mentions (10)

  • 5 Best Practices For Data Integration To Boost ROI And Efficiency
    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: over 1 year ago
  • What compute service i should use? Advice for a duck-tape kind of guy
    I'm going to guess you want something like EMR. Which can take large data sets segment it across multiple executors and coalesce the data back into a final dataset. Source: almost 2 years ago
  • Processing a large text file containing millions of records.
    This is exactly the kind of workload EMR was made for, you can even run it serverless nowadays. Athena might be a viable option as well. Source: about 2 years ago
  • How to use Spark and Pandas to prepare big data
    Apache Spark is one of the most actively developed open-source projects in big data. The following code examples require that you have Spark set up and can execute Python code using the PySpark library. The examples also require that you have your data in Amazon S3 (Simple Storage Service). All this is set up on AWS EMR (Elastic MapReduce). - Source: dev.to / over 2 years ago
  • Beginner building a Hadoop cluster
    Check out https://aws.amazon.com/emr/. Source: about 2 years ago
View more

What are some alternatives?

When comparing Kylo and Amazon EMR, you can also consider the following products

IRI Voracity - IRI Voracity is an automated data management platform that helps you extract, transform and load (ETL) your data lake to any data warehouse or cloud.

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

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).

Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.

Zaloni Data Platform - Get self-service data from a platform that accelerates business insights. Use data from any source, anywhere: the cloud, on-premises, multi-cloud or hybrid.

Google Cloud Dataproc - Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost

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