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Amazon EMR VS IBM Cloud Object Storage

Compare Amazon EMR VS IBM Cloud Object Storage and see what are their differences

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Amazon EMR logo Amazon EMR

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

IBM Cloud Object Storage logo IBM Cloud Object Storage

IBM Cloud Object Storage is a platform that offers cost-effective and scalable cloud storage for unstructured data.
  • Amazon EMR Landing page
    Landing page //
    2023-04-02
  • IBM Cloud Object Storage Landing page
    Landing page //
    2023-09-18

Amazon EMR features and specs

  • Scalability
    Amazon EMR makes it easy to provision one, hundreds, or thousands of compute instances in minutes. You can easily scale your cluster up or down based on your needs.
  • Cost-effectiveness
    You only pay for what you use with EMR. There are no upfront fees. You can also leverage EC2 Spot Instances for a more cost-effective solution.
  • Ease of Use
    Amazon EMR has a user-friendly interface and integrates with a wide range of AWS services, making it easy to set up and manage big data frameworks like Apache Hadoop, Spark, etc.
  • Managed Service
    Amazon EMR takes care of the setup, configuration, and tuning of the big data environments, allowing you to focus on your data processing rather than managing infrastructure.
  • Security
    EMR integrates with AWS security features such as IAM for fine-grained access control, encryption options, and Virtual Private Cloud (VPC) for network security.
  • Flexibility
    Supports multiple big data frameworks including Hadoop, Spark, HBase, Presto, and more, facilitating a wide range of use cases.

Possible disadvantages of Amazon EMR

  • Complex Pricing Model
    EMR's pricing can be complex with costs varying based on instance types, storage, and data transfer. Predicting costs may be challenging.
  • Data Transfer Costs
    If your applications require transferring large amounts of data in and out of EMR, the associated costs can be significant.
  • Learning Curve
    Although EMR is easier to manage compared to on-premises solutions, there is still a learning curve associated with mastering the service and optimizing its various settings.
  • Vendor Lock-in
    Since EMR is an AWS service, you may find it difficult to migrate to another service or cloud provider without significant re-engineering.
  • Dependency on AWS Ecosystem
    The full potential of EMR is best realized when integrated with other AWS services. This can be limiting if your architecture uses services from multiple cloud providers.

IBM Cloud Object Storage features and specs

  • Scalability
    IBM Cloud Object Storage offers very high scalability, allowing businesses to store large amounts of data easily. This flexibility is crucial for businesses that are growing their storage needs or have fluctuating demands.
  • Data Resiliency
    The service provides robust data resiliency options, including geo-dispersed storage configurations, enabling enhanced protection against data loss and improved availability.
  • Cost Efficiency
    With its flexible pricing model, businesses can choose options that best fit their budget, such as 'Pay-as-you-go' plans, thereby optimizing costs according to actual usage.
  • Security Features
    It comes with comprehensive security features, including encryption, access control, and integration with IAM policies, ensuring that data is protected both at rest and in transit.
  • Integration
    Seamless integration with the broader IBM Cloud ecosystem, as well as other cloud services and applications, allows businesses to easily incorporate this storage solution into their existing cloud strategy.

Possible disadvantages of IBM Cloud Object Storage

  • Complexity
    The extensive feature set and customization options might lead to a steeper learning curve for new users or smaller teams without dedicated IT resources.
  • Performance Variability
    Depending on the region and specific use case, users might encounter variability in performance, particularly in scenarios requiring low-latency or high-throughput data access.
  • Support Availability
    While IBM offers various support plans, certain users might find the support mechanisms, such as community forums and basic plans, less responsive compared to some other providers.
  • Pricing Complexity
    Although pricing models are flexible, they can also become complex and convoluted, making it difficult for some businesses to predict costs precisely without detailed monitoring and analysis.
  • Limited Proprietary Tooling
    Compared to some competitors, IBM might have fewer proprietary tools and native applications directly integrated with their cloud storage, potentially requiring additional third-party tools or custom development for specific needs.

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

IBM Cloud Object Storage videos

+ Add

IBM Cloud Object Storage: Built for business

More videos:

  • Review - Getting Started with IBM Cloud Object Storage
  • Review - IBM Cloud Object Storage webinar

Category Popularity

0-100% (relative to Amazon EMR and IBM Cloud Object Storage)

Amazon EMR

IBM Cloud Object Storage

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

User comments

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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.

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 2 years 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 3 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 3 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 3 years ago
  • Beginner building a Hadoop cluster
    Check out https://aws.amazon.com/emr/. Source: about 3 years ago
View more

IBM Cloud Object Storage mentions (0)

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

What are some alternatives?

When comparing Amazon EMR and IBM Cloud Object Storage, you can also consider the following products

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

Alibaba Object Storage Service - Alibaba Object Storage Service is an encrypted and secure cloud storage service which stores, processes and accesses massive amounts of data

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

Wasabi Cloud Object Storage - Storage made simple. Faster than Amazon's S3. Less expensive than Glacier.

Qubole - Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.

Contabo Object Storage - S3-compatible cloud object storage with unlimited, free transfer at a fraction of what others charge. Easy migration & predictable billing. Sign up now & save.

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