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Azure Blob Storage VS Amazon EMR

Compare Azure Blob Storage VS Amazon EMR and see what are their differences

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Contents:
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  2. » Videos
  3. » Reviews
  4. » Alternatives

Azure Blob Storage logo Azure Blob Storage

Use Azure Blob Storage to store all kinds of files. Azure hot, cool, and archive storage is reliable cloud object storage for unstructured data

Amazon EMR logo Amazon EMR

Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.
  • Azure Blob Storage Landing page
    Landing page //
    2023-04-01
  • Amazon EMR Landing page
    Landing page //
    2023-04-02

Azure Blob Storage videos

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Amazon EMR videos

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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 Azure Blob Storage and Amazon EMR)

Azure Blob Storage

Amazon EMR

Cloud Storage
100 100%
Cloud Storage
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100
Cloud Computing
100 100%
Cloud Computing
0% 0
Big Data
0 0%
Big Data
100% 100

User comments

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Social recommendations and mentions

Azure Blob Storage might be a bit more popular than Amazon EMR. We know about 13 links to it since March 2021 and only 10 links to Amazon EMR. 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.

Azure Blob Storage mentions (13)

  • How to Choose the Right MQTT Data Storage for Your Next Project
    Azure Blob Storage{:target="_blank"} is a scalable and highly available object storage service provided by Microsoft Azure. They offer various storage tiers, so you can optimize cost and performance based on your requirements. They also provides features like lifecycle management, versioning, and data encryption. - Source: dev.to / 11 months ago
  • How to build a data pipeline using Delta Lake
    An object storage system (e.g. Amazon S3, Azure Blob Storage, Google Cloud Platform Cloud Storage, etc.) makes it easy and simple to save large amounts of historical data and retrieve it for future use. - Source: dev.to / about 1 year ago
  • Azure Functions: unzip large files
    I want to share my experience unzipping large files stored in Azure Blob Storage using Azure Functions with Node.js. - Source: dev.to / over 1 year ago
  • How to move my work from Heroku to Azure
    - Optionally, use Blob Storage to host static content. Then you can add Azure CDN for faster access to it. Source: over 1 year ago
  • If you need a sql database how do you make on, populate it with preexisting data, and add/delete from it?
    Alright so this one? https://azure.microsoft.com/en-us/services/storage/blobs/. Source: almost 2 years ago
View more

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 Azure Blob Storage and Amazon EMR, you can also consider the following products

Minio - Minio is an open-source minimal cloud storage server.

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

Google Cloud Storage - Google Cloud Storage offers developers and IT organizations durable and highly available object storage.

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

Amazon S3 - Amazon S3 is an object storage where users can store data from their business on a safe, cloud-based platform. Amazon S3 operates in 54 availability zones within 18 graphic regions and 1 local region.

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

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