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  1. Stackups
  2. Application & Data
  3. Databases
  4. Big Data As A Service
  5. Amazon EMR vs Cloudera Enterprise

Amazon EMR vs Cloudera Enterprise

OverviewComparisonAlternatives

Overview

Amazon EMR
Amazon EMR
Stacks542
Followers682
Votes54
Cloudera Enterprise
Cloudera Enterprise
Stacks126
Followers172
Votes5

Amazon EMR vs Cloudera Enterprise: What are the differences?

Key Differences between Amazon EMR and Cloudera Enterprise

Amazon EMR and Cloudera Enterprise are two popular big data platforms used for processing and analyzing large datasets. While both offer similar capabilities, there are significant differences between the two:

  1. Pricing Model:

    • Amazon EMR: Amazon EMR follows a pay-as-you-go pricing model, allowing users to be billed based on the actual resources used.
    • Cloudera Enterprise: Cloudera Enterprise has a subscription-based pricing model, where users pay a fixed amount for a set duration, regardless of resource utilization.
  2. Cloud Support:

    • Amazon EMR: As an Amazon Web Services (AWS) offering, Amazon EMR is fully integrated with other AWS services and provides seamless integration with the AWS ecosystem.
    • Cloudera Enterprise: Cloudera Enterprise can be deployed on various cloud providers, including AWS, but it does not have the same level of integration with other cloud services.
  3. Managed Service vs Self-Managed:

    • Amazon EMR: Amazon EMR is a fully managed service, meaning that AWS takes care of the underlying infrastructure, patching, and maintenance, allowing users to focus solely on data processing.
    • Cloudera Enterprise: Cloudera Enterprise requires users to manage the infrastructure themselves, giving them more control and flexibility but also requiring additional time and resources for maintenance.
  4. Ecosystem:

    • Amazon EMR: With Amazon EMR, users have access to a wide range of pre-built Amazon EMR-specific applications and integrations, making it easier to set up and work with big data solutions.
    • Cloudera Enterprise: Cloudera Enterprise provides a comprehensive ecosystem with a rich set of tools and applications, including software from Cloudera as well as third-party vendors. It offers more flexibility in terms of application selection.
  5. Integration with Hadoop Distributions:

    • Amazon EMR: Amazon EMR supports various Hadoop distributions, including the Apache Hadoop provided by default, as well as other popular distributions such as Hortonworks and Cloudera.
    • Cloudera Enterprise: Cloudera Enterprise is built on Cloudera's own distribution of Apache Hadoop and offers deep integration with their specific Hadoop stack.
  6. Security and Governance:

    • Amazon EMR: Amazon EMR provides built-in security features, including encryption, access control, and integration with AWS Identity and Access Management (IAM), ensuring data privacy and compliance.
    • Cloudera Enterprise: Cloudera Enterprise offers robust security and governance features, including data access controls, auditing capabilities, and integration with enterprise security solutions.

In summary, Amazon EMR and Cloudera Enterprise differ in their pricing models, cloud support, management approach, ecosystem offerings, integration with Hadoop distributions, and security features. Users must consider these differences to choose the platform that best fits their needs and requirements.

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Detailed Comparison

Amazon EMR
Amazon EMR
Cloudera Enterprise
Cloudera Enterprise

It is used in a variety of applications, including log analysis, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics.

Cloudera Enterprise includes CDH, the world’s most popular open source Hadoop-based platform, as well as advanced system management and data management tools plus dedicated support and community advocacy from our world-class team of Hadoop developers and experts.

Elastic- Amazon EMR enables you to quickly and easily provision as much capacity as you need and add or remove capacity at any time. Deploy multiple clusters or resize a running cluster;Low Cost- Amazon EMR is designed to reduce the cost of processing large amounts of data. Some of the features that make it low cost include low hourly pricing, Amazon EC2 Spot integration, Amazon EC2 Reserved Instance integration, elasticity, and Amazon S3 integration.;Flexible Data Stores- With Amazon EMR, you can leverage multiple data stores, including Amazon S3, the Hadoop Distributed File System (HDFS), and Amazon DynamoDB.;Hadoop Tools- EMR supports powerful and proven Hadoop tools such as Hive, Pig, and HBase.
Unified – one integrated system, bringing diverse users and application workloads to one pool of data on common infrastructure; no data movement required;Secure – perimeter security, authentication, granular authorization, and data protection;Governed – enterprise-grade data auditing, data lineage, and data discovery;Managed – native high-availability, fault-tolerance and self-healing storage, automated backup and disaster recovery, and advanced system and data management;Open – Apache-licensed open source to ensure your data and applications remain yours, and an open platform to connect with all of your existing investments in technology and skills
Statistics
Stacks
542
Stacks
126
Followers
682
Followers
172
Votes
54
Votes
5
Pros & Cons
Pros
  • 15
    On demand processing power
  • 12
    Don't need to maintain Hadoop Cluster yourself
  • 7
    Hadoop Tools
  • 6
    Elastic
  • 4
    Backed by Amazon
Pros
  • 1
    Hybrid cloud
  • 1
    Multicloud
  • 1
    Scalability
  • 1
    Cheeper
  • 1
    Easily management

What are some alternatives to Amazon EMR, Cloudera Enterprise?

Google BigQuery

Google BigQuery

Run super-fast, SQL-like queries against terabytes of data in seconds, using the processing power of Google's infrastructure. Load data with ease. Bulk load your data using Google Cloud Storage or stream it in. Easy access. Access BigQuery by using a browser tool, a command-line tool, or by making calls to the BigQuery REST API with client libraries such as Java, PHP or Python.

Amazon Redshift

Amazon Redshift

It is optimized for data sets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.

Qubole

Qubole

Qubole is a cloud based service that makes big data easy for analysts and data engineers.

Altiscale

Altiscale

we run Apache Hadoop for you. We not only deploy Hadoop, we monitor, manage, fix, and update it for you. Then we take it a step further: We monitor your jobs, notify you when something’s wrong with them, and can help with tuning.

Snowflake

Snowflake

Snowflake eliminates the administration and management demands of traditional data warehouses and big data platforms. Snowflake is a true data warehouse as a service running on Amazon Web Services (AWS)—no infrastructure to manage and no knobs to turn.

Stitch

Stitch

Stitch is a simple, powerful ETL service built for software developers. Stitch evolved out of RJMetrics, a widely used business intelligence platform. When RJMetrics was acquired by Magento in 2016, Stitch was launched as its own company.

Azure Synapse

Azure Synapse

It is an analytics service that brings together enterprise data warehousing and Big Data analytics. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources—at scale. It brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs.

Dremio

Dremio

Dremio—the data lake engine, operationalizes your data lake storage and speeds your analytics processes with a high-performance and high-efficiency query engine while also democratizing data access for data scientists and analysts.

Airbyte

Airbyte

It is an open-source data integration platform that syncs data from applications, APIs & databases to data warehouses lakes & DBs.

Treasure Data

Treasure Data

Treasure Data's Big Data as-a-Service cloud platform enables data-driven businesses to focus their precious development resources on their applications, not on mundane, time-consuming integration and operational tasks. The Treasure Data Cloud Data Warehouse service offers an affordable, quick-to-implement and easy-to-use big data option that does not require specialized IT resources, making big data analytics available to the mass market.

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