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  4. Big Data As A Service
  5. Azure HDInsight vs Cloudera Enterprise

Azure HDInsight vs Cloudera Enterprise

OverviewComparisonAlternatives

Overview

Cloudera Enterprise
Cloudera Enterprise
Stacks126
Followers172
Votes5
Azure HDInsight
Azure HDInsight
Stacks29
Followers138
Votes0

Azure HDInsight vs Cloudera Enterprise: What are the differences?

<Write Introduction here>

1. **Deployment Options**: Azure HDInsight is a fully managed cloud service provided by Microsoft, while Cloudera Enterprise is an on-premises solution that requires in-house infrastructure and resources for deployment and maintenance.
2. **Scalability**: Azure HDInsight is designed to easily scale up or down based on the processing needs, making it a suitable choice for dynamic workloads. On the other hand, Cloudera Enterprise may require additional hardware procurement and configuration for scaling, which can be more time-consuming.
3. **Integration with Azure Services**: Azure HDInsight seamlessly integrates with other Azure services such as Azure Data Lake Storage, Azure Synapse Analytics, and Power BI, enabling a comprehensive data analytics ecosystem. In comparison, Cloudera Enterprise may have limited integration with external cloud services, making the setup less flexible.
4. **Cost Structure**: Azure HDInsight follows a pay-as-you-go model, allowing users to pay only for the resources they consume. In contrast, Cloudera Enterprise may involve upfront hardware investments and fixed maintenance costs, regardless of the actual data processing usage.
5. **Security Features**: Azure HDInsight offers built-in security features such as encryption, Active Directory integration, and network isolation, ensuring data protection in the cloud environment. While Cloudera Enterprise provides security features, additional configurations and monitoring may be required to achieve the same level of security as in Azure HDInsight.
6. **Technical Support**: Azure HDInsight includes support from Microsoft as part of the service, offering rapid response times and expert assistance. Cloudera Enterprise may require a separate support contract for technical issues, potentially leading to delays in problem resolution.

In Summary, Azure HDInsight and Cloudera Enterprise differ in deployment options, scalability, integration with cloud services, cost structure, security features, and technical support. Azure HDInsight offers a fully managed cloud service with seamless integration and pay-as-you-go pricing, while Cloudera Enterprise requires on-premises deployment and may involve higher setup and maintenance costs.

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Detailed Comparison

Cloudera Enterprise
Cloudera Enterprise
Azure HDInsight
Azure HDInsight

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.

It is a cloud-based service from Microsoft for big data analytics that helps organizations process large amounts of streaming or historical data.

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
Fully managed; Full-spectrum; Open-source analytics service in the cloud for enterprises
Statistics
Stacks
126
Stacks
29
Followers
172
Followers
138
Votes
5
Votes
0
Pros & Cons
Pros
  • 1
    Cheeper
  • 1
    Easily management
  • 1
    Hybrid cloud
  • 1
    Multicloud
  • 1
    Scalability
No community feedback yet
Integrations
No integrations available
IntelliJ IDEA
IntelliJ IDEA
Apache Spark
Apache Spark
Kafka
Kafka
Visual Studio Code
Visual Studio Code
Hadoop
Hadoop
Apache Storm
Apache Storm
HBase
HBase
Apache Hive
Apache Hive
Azure Data Factory
Azure Data Factory
Azure Active Directory
Azure Active Directory

What are some alternatives to Cloudera Enterprise, Azure HDInsight?

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.

Apache Spark

Apache Spark

Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.

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.

Presto

Presto

Distributed SQL Query Engine for Big Data

Amazon EMR

Amazon EMR

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

Amazon Athena

Amazon Athena

Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.

Apache Flink

Apache Flink

Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.

lakeFS

lakeFS

It is an open-source data version control system for data lakes. It provides a “Git for data” platform enabling you to implement best practices from software engineering on your data lake, including branching and merging, CI/CD, and production-like dev/test environments.

Druid

Druid

Druid is a distributed, column-oriented, real-time analytics data store that is commonly used to power exploratory dashboards in multi-tenant environments. Druid excels as a data warehousing solution for fast aggregate queries on petabyte sized data sets. Druid supports a variety of flexible filters, exact calculations, approximate algorithms, and other useful calculations.

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