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IBM DataStage VS Amazon EMR

Compare IBM DataStage VS Amazon EMR and see what are their differences

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IBM DataStage logo IBM DataStage

Extract, transfer and load ETL data across multiple systems, with support forextended metadata management and big data enterprise connectivity.

Amazon EMR logo Amazon EMR

Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.
  • IBM DataStage Landing page
    Landing page //
    2023-07-15
  • Amazon EMR Landing page
    Landing page //
    2023-04-02

IBM DataStage videos

+ Add

IBM InfoSphere DataStage Skill Builder Part 1: How to build and run a DataStage parallel job

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 IBM DataStage and Amazon EMR)

IBM DataStage

Amazon EMR

Data Integration
100 100%
Data Integration
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100
ETL
100 100%
ETL
0% 0
Big Data
0 0%
Big Data
100% 100

User comments

Share your experience with using IBM DataStage and Amazon EMR. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare IBM DataStage and Amazon EMR

IBM DataStage Reviews

10 Best ETL Tools (October 2023)
IBM DataStage is an excellent data integration tool that is focused on a client-server design. It extracts, transforms, and loads data from a source to a target. These sources can include files, archives, business apps, and more.
Source: www.unite.ai
A List of The 16 Best ETL Tools And Why To Choose Them
Infosphere Datastage is an ETL tool offered by IBM as part of its Infosphere Information Server ecosystem. With its graphical framework, users can design data pipelines that extract data from multiple sources, perform complex transformations, and deliver the data to target applications.
Source: www.datacamp.com
Top 10 AWS ETL Tools and How to Choose the Best One | Visual Flow
DataStage is an IBM proprietary tool that extracts, transforms, and loads data from a source to the destination storage. It is suitable for on-premises deployment and use in hybrid or multi-cloud environments. Data sources that DataStage is compatible with include sequential files, indexed files, relational databases, external data sources, archives, enterprise applications,...
Source: visual-flow.com

Amazon EMR Reviews

We have no reviews of Amazon EMR yet.
Be the first one to post

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.

IBM DataStage mentions (0)

We have not tracked any mentions of IBM DataStage yet. Tracking of IBM DataStage recommendations started around Mar 2021.

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: about 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: almost 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
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What are some alternatives?

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

Azure Data Factory - Learn more about Azure Data Factory, the easiest cloud-based hybrid data integration solution at an enterprise scale. Build data factories without the need to code.

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

Striim - Striim provides an end-to-end, real-time data integration and streaming analytics platform.

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

Apache NiFi - An easy to use, powerful, and reliable system to process and distribute data.

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

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