Software Alternatives, Accelerators & Startups

Amazon EMR VS Google Cloud Machine Learning

Compare Amazon EMR VS Google Cloud Machine Learning and see what are their differences

Amazon EMR logo Amazon EMR

Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.

Google Cloud Machine Learning logo Google Cloud Machine Learning

Google Cloud Machine Learning is a service that enables user to easily build machine learning models, that work on any type of data, of any size.
  • Amazon EMR Landing page
    Landing page //
    2023-04-02
  • Google Cloud Machine Learning Landing page
    Landing page //
    2023-09-12

Amazon EMR videos

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

Google Cloud Machine Learning videos

No Google Cloud Machine Learning videos yet. You could help us improve this page by suggesting one.

+ Add video

Category Popularity

0-100% (relative to Amazon EMR and Google Cloud Machine Learning)
Data Dashboard
100 100%
0% 0
Data Science And Machine Learning
Big Data
100 100%
0% 0
Data Science Tools
0 0%
100% 100

User comments

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Social recommendations and mentions

Based on our record, Google Cloud Machine Learning should be more popular than Amazon EMR. It has been mentiond 21 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.

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: 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

Google Cloud Machine Learning mentions (21)

  • Gemini 1.5 outshines GPT-4-Turbo-128K on long code prompts, HVM author
    2. Google Cloud Vertex AI: https://cloud.google.com/vertex-ai. Policy: https://cloud.google.com/vertex-ai/docs/generative-ai/data-governance#foundation_model_training. - Source: Hacker News / 4 months ago
  • Let's build your first ML app in Google Cloud Run
    Google Cloud Platform (GCP) provides a very befitting Machine Learning solution called Vertex Ai that handles Google Cloud's unified platform for building, deploying, and managing machine learning (ML) models. Our goal is to build a simple Machine Learning application that optimizes all that GCP provides plus an implementation of continuous integration and continuous development (CI/CD). - Source: dev.to / 5 months ago
  • Google Gemini Pro API Available Through AI Studio
    Cross posting some links from another post that HNers found helpful - https://cloud.google.com/vertex-ai (marketing page) - https://cloud.google.com/vertex-ai/docs (docs entry point) - https://console.cloud.google.com/vertex-ai (cloud console) - https://console.cloud.google.com/vertex-ai/model-garden (all the models) - https://console.cloud.google.com/vertex-ai/generative (studio / playground) VertexAI is the... - Source: Hacker News / 6 months ago
  • Google Imagen 2
    For the peer comments - https://cloud.google.com/vertex-ai (main page) - https://cloud.google.com/vertex-ai/docs/start/introduction-unified-platform (docs entry point) - https://console.cloud.google.com/vertex-ai (cloud console). - Source: Hacker News / 6 months ago
  • Introducing Gemini: our largest and most capable AI model
    Starting on December 13, developers and enterprise customers can access Gemini Pro via the Gemini API in Google AI Studio or Google Cloud Vertex AI. Source: 6 months ago
View more

What are some alternatives?

When comparing Amazon EMR and Google Cloud Machine Learning, you can also consider the following products

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

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

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

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?

NumPy - NumPy is the fundamental package for scientific computing with Python