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AWS Lake Formation vs Apache Beam vs Amazon EMR - Which Tool Fits Your Business?

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TL;DR - Quick Comparison Summary

Description

AWS Lake Formation is a powerful tool that simplifies the process of gathering, categorizing and transferring secure data from databases and object storage to a data lake. This programme ... Read More

Apache Beam is an advanced open-source unified programming model, specifically designed for defining both batch and streaming data-parallel processing pipelines. It supports data sets of ... Read More

Introducing Amazon EMR, the leading big data platform in the cloud. With a powerful combination of open-source tools such as Apache Spark, Hive, HBase, Flink, Hudi, and Presto, EMR makes it ... Read More

Entry Level Pricing

  • Not Available
  • Not Available
  • Starts from $0.04

Free Trial Availability

  • No free trial
  • No free trial
  • No free trial

User Ratings

4.3

(3)

4.2

(93)
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Software Demo

Demo

How do AWS Lake Formation, Apache Beam and Amazon EMR Compare on Features?

Total Features

9 Features

5 Features

0 Features

Unique Features

      No features

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      What Do AWS Lake Formation, Apache Beam and Amazon EMR Cost?

      Pricing Option

            Starting From

            • Not Available
            • Not Available
            • $0.04

            Pricing Plans

            • Not Available
            • Not Available
            • Not Available

            Other Details

            Organization Types supported

            • Large Enterprises
            • Small Business
            • Medium Business
            • Large Enterprises
            • Small Business
            • Medium Business
            • Large Enterprises
            • Small Business
            • Medium Business

            Platforms Supported

            • Browser Based (Cloud)
            • Browser Based (Cloud)
            • Browser Based (Cloud)
            • Browser Based (Cloud)
            • Browser Based (Cloud)
            • Browser Based (Cloud)

            Modes of support

            • 24/7 (Live rep)
            • Business Hours
            • Online
            • 24/7 (Live rep)
            • Business Hours
            • Online
            • 24/7 (Live rep)
            • Business Hours
            • Online

            API Support

            • Not Available
            • Available
            • Available
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            AWS Lake Formation vs Apache Beam User Reviews & Rating Comparison

            User Ratings

            Rating Distribution

            Excellent

            24

            Very Good

            26

            Good

            0

            Poor

            0

            Terible

            0

            Excellent

            18

            Very Good

            2

            Good

            0

            Poor

            0

            Terible

            0

            Excellent

            38

            Very Good

            22

            Good

            1

            Poor

            1

            Terible

            1

            Expert's Review generated by AI

            No Expert ai Review available for the product

            No Expert ai Review available for the product

            Amazon EMR stands out as a versatile and powerful solution for running a variety of applications like Apache Spark, Flink, and Trino in a streamlined manner. Users commend its ease of launching ...Read more

            Pros and Cons

            Pros and Cons of AWS Lake Formation

            Pros and Cons of Apache Beam

            Pros and Cons of Amazon EMR

            • Ease of launching or cloning EMR clusters and scaling based on various parameters like containers, CPU, etc.

            • Supports widely used applications like Spark, Hive, Hadoop, Flink, etc.

            • Provides easy configuration control and debugging support.

            • Improved workloads' speed leading to more time for code refinement.

            • Working with Spot instances can be complicated, especially during unavailability.

            • Lack of features like auto-completion in the notebook interface.

            Positive Reviews

            No reviews available for the product

            No reviews available for the product

            No reviews available for the product

            List of Customers

            Customers

            Panasonic

            Panasonic

            Zalando

            Zalando

            Life360

            Life360

            No Customers information available.

            Expedia

            Expedia

            Nasdaq

            Nasdaq

            Finra

            Finra

            Media and Screenshots

            Screenshots

            Lake Formation Blueprint Incremental

            2 Screenshots

            No screenshots available.

            No screenshots available.

            Videos

            video-0

            2 Videos

            video-0

            3 Videos

            video-0

            3 Videos

            Frequently Asked Questions (FAQs)

            Stuck on something? We're here to help with all the questions and answers in one place.

            Neither AWS Lake Formation nor Apache Beam offers a free trial.

            AWS Lake Formation is designed for Large Enterprises, Medium Business and Small Business.

            Apache Beam is designed for Large Enterprises, Medium Business and Small Business.

            Pricing details for both AWS Lake Formation and Apache Beam are unavailable at this time. Contact the respective providers for more information.

            Some top alternatives to AWS Lake Formation includes Snowflake, SAS Advanced Analytics, Qualified, Datascale, Workvivo, DataSquirrel, Azure Data Lake Analytics, Infor Data Lake, SAS Data Quality, Databricks, Dataiku DSS and Dremio.

            Some top alternatives to Apache Beam includes Spark NLP, Ascend, Qualified, Pluralsight Flow, Workvivo, Seqera Labs, SparkLight, Confluent, Datos Intelligence, Lenses, Databricks and Dataform.

            Disclaimer: This research has been collated from a variety of authoritative sources. We welcome your feedback at [email protected].

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