Big data analysis with Hadoop is a need of every organization dealing with big data computing. The momentum gained by the big data analysis is actually because of the Hadoop. The Hadoop is evolving, and the new version of Hadoop has almost double storage capacity compared to before, and there are many more exciting features. Hadoop has a bright future in the space of big data technology. It is a pertaining question: what’s better, Cloudera or Hortonworks?
Hadoop Distribution: Cloudera or Hortonworks
There is a demand for Hadoop professionals who are specialized and trained in a particular Hadoop distribution. Almost all companies use either Cloudera or Hortonworks as a distribution platform. Both Cloudera and Hortonworks are built on Apache Hadoop. It indicates that there must be some similarities as well as differences between both of these platforms. Let us check them out one after another.
Similarities
- Cloudera and Hortonworks are both Hadoop Distributions used for enterprises.
- These distributions are secure and stable.
- Both Cloudera and Hortonworks have an active community, which helps in troubleshooting the problems.
- Both of them have a robust platform where professionals can excel in their skills and get certified as a Hadoop Professional.
- Both are based on a shared-nothing architecture.
- Both are based on master-slave architecture when it comes to distribution wise.
- Both of them support – MapReduce and YARN.
Differences
As mentioned earlier, both Cloudera and Hortonworks are built on Apache Hadoop. However, there are a few differences, as listed below:
- Hortonworks possesses an open-source license. On the other hand, Clouder is used for commercial purposes; it has a commercial right. Thus, the business growth strategy for both of them varies entirely.
- Cloudera is a paid service (provides a free trial for a limited period), and Hortonworks is entirely free as it is an open-source distribution.
- The technological strategies followed by both Cloudera and Hortonworks are altogether different.
- Cloudera competes with the other commercial software providers and hence has aggressive business strategies. Hortonworks, on the other hand, focuses on embedding on existing data platforms.
- Windows server is a native component for Hortonworks distribution. Windows server is not a native component for Cloudera CDH, but it runs on the windows server.
Hadoop Distribution in Industry
Hortonworks and Cloudera have their respective advantages and disadvantages. Hence, companies should measure a few factors for both the distributions before finalizing. These factors should be calculated based on long and short-term goals:
- Scalability
- Performance
- Reliability
- Manageability
- Data Access
Considering some parameters related to the organization is also essential before selecting the Hadoop Distribution. Few of them could be:
- Expanded Functionality
- Technical Support
- Flexibility
- System Dependency
- Cost
As a Hadoop Distribution vendor, both Cloudera and Hortonworks are market leaders, undoubtedly. They are both helping to grow the big data arena by being innovative. Hortonworks is coping up fastly as Cloudera, with its paid components, has been a contender in this niche for a long time now. Lastly, it depends on the company and its primary factors while choosing Hortonworks or Cloudera for Hadoop Distribution. The Hadoop course will help you to get every necessary information on Hadoop.
Market Advancements: Cloudera or Hortonworks
“Who among these advances the market, Cloudera or Hortonworks?” is indeed a
pertaining question. Cloudera is more prevalent in the market as compared to the Hortonworks. There are many reasons why it is bragged about in the market. Cloudera has made a commendable contribution to the Apache Hadoop project. Not limited to this, the distribution through Cloudera is a high profile. It is also well accepted in big data organizations. Cloudera is continuously upgrading in this field, and its application in the enterprise is increasing as it meets the organization’s needs. Sentry – recently launched by Cloudera, is a significant step in the field of concern of organizations: data security.
There is another one of the crucial reasons (related to the sub-project) why Cloudera is a preferred distribution.
The CMS (Cloudera Management Suite) consists of automated and tool-based Hadoop deployment capabilities, enterprise-level features, using its resource management module for capacity and expansion planning, and configuration management with dashboards.
Whereas similar to the Cloudera Management Suite or CMS, Hortonworks has Ambari. Ambari is not as advanced and mature as Cloudera Management Suite is. It also lacks many cluster managements’ features.
Both Hortonworks and Cloudera come with open-source Apache Hadoop. Cloudera also comes with Vendor-Lock Management Suite, which provides fast deployment and installment processes. However, Hortonworks has quicker updates than Cloudera since it is a hundred percent open source. The Hadoop course will suggest the best distribution in the market.
Scope of Hadoop Certifications
Both Cloudera and Hortonworks provide different types of certifications with different levels. It can be concluded that they are different regarding the following factors: Distribution specific, Complexity, Preparation, Area of Expertise, Exam Pattern, Cost, etc.
There are many Cloudera Hadoop Certifications like:
- Cloudera Spark and Hadoop Developer (CCA175): This certification is focused on executing a Hadoop cluster and Spark Applications.
- CCA Data Analyst (CCA 159): This certification focuses on data preparation, unstructured data formatting, data analysis.
- CCA Administrator (CCA – 131): Focuses on using Cloudera for administration related aspects, installation, and configuration in Hadoop Cluster.
The types of Hortonworks Certifications are as given:
- HDP Certified Developer (HDPCD): This certification is focused on data transformation, data ingestion, and data analysis.
- HDP Certified Apache Spark Developer (HDPDC – Spark): This certification is focused on developing spark applications using Scala or Python to build Spark applications through Spark SQL and Spark Core.
- HDP CERTIFIED JAVA DEVELOPER (HDPCD – Java): This certification focuses on Java developers. The questions are mostly Hadoop related functions like creating partitioners, combiners, custom sorting, custom keys, and joining of data sets.
- HDP Certified Administrator (HDPCA): Focuses on Hadoop Cluster like installation, troubleshooting, security, high availability, and configuration.
- Hortonworks Certified Associate (HCA): Focuses on Data Access, Operations, Data governance and workflow, and security.
Conclusion
Hadoop certified professionals always have the edge over other applicants, and hence it is suggested to look for a Hadoop course that will make you an expert in all the required skills.