Apache Spark vs Cloudera Distribution for Hadoop comparison

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2,498 views|1,884 comparisons
89% willing to recommend
Cloudera Logo
2,959 views|2,278 comparisons
91% willing to recommend
Comparison Buyer's Guide
Executive Summary

We performed a comparison between Apache Spark and Cloudera Distribution for Hadoop based on real PeerSpot user reviews.

Find out in this report how the two Hadoop solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
To learn more, read our detailed Apache Spark vs. Cloudera Distribution for Hadoop Report (Updated: March 2024).
768,578 professionals have used our research since 2012.
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"Now, when we're tackling sentiment analysis using NLP technologies, we deal with unstructured data—customer chats, feedback on promotions or demos, and even media like images, audio, and video files. For processing such data, we rely on PySpark. Beneath the surface, Spark functions as a compute engine with in-memory processing capabilities, enhancing performance through features like broadcasting and caching. It's become a crucial tool, widely adopted by 90% of companies for a decade or more.""With Hadoop-related technologies, we can distribute the workload with multiple commodity hardware.""It provides a scalable machine learning library.""With Spark, we parallelize our operations, efficiently accessing both historical and real-time data.""We use Spark to process data from different data sources.""The good performance. The nice graphical management console. The long list of ML algorithms.""The most valuable feature of Apache Spark is its ease of use.""The most valuable feature of Apache Spark is its flexibility."

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"We experienced many issues when we started working with Hadoop 3.0 in the Cloudera 6.0 version, so there are a lot of things that need to improve. I believe they are working on that.""Cloudera is a very manageable solution with good support.""The search function is the most valuable aspect of the solution.""We're now able to store large volumes of data through Cloudera Distribution for Hadoop. We're able to push large volumes of data to the platform, and that used to be a challenge, especially when storing a terabyte of information. This is the area where Cloudera Distribution for Hadoop improved the organization.""The file system is a valuable feature.""The solution is reliable and stable, it fits our requirements.""It has the best proxy, security, and support features compared to open-source products.""The product as a whole is good."

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Cons
"When you want to extract data from your HDFS and other sources then it is kind of tricky because you have to connect with those sources.""The migration of data between different versions could be improved.""It would be beneficial to enhance Spark's capabilities by incorporating models that utilize features not traditionally present in its framework.""Apache Spark could potentially improve in terms of user-friendliness, particularly for individuals with a SQL background. While it's suitable for those with programming knowledge, making it more accessible to those without extensive programming skills could be beneficial.""I know there is always discussion about which language to write applications in and some people do love Scala. However, I don't like it.""The logging for the observability platform could be better.""When you are working with large, complex tasks, the garbage collection process is slow and affects performance.""There could be enhancements in optimization techniques, as there are some limitations in this area that could be addressed to further refine Spark's performance."

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"Cloudera Distribution for Hadoop has a limited feature list and a lot of costs involved.""There is a maximum of a one-gigabyte block size, which is an area of storage that can be improved upon.""The dashboard could be improved.""We experienced many issues when we started working with Hadoop 3.0 in the Cloudera 6.0 version, so there is a lot of things that need to improve.""The one thing that we struggled with predominately was support. Because it was relatively new, support was always a big issue and I think it's still a bit of an ongoing concern with the team currently managing it.""The Cloudera training has deteriorated significantly.""Cloudera Distribution for Hadoop is not always completely stable in some cases, which can be a concern for big data solutions.""This is a very expensive solution."

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Pricing and Cost Advice
  • "Since we are using the Apache Spark version, not the data bricks version, it is an Apache license version, the support and resolution of the bug are actually late or delayed. The Apache license is free."
  • "Apache Spark is open-source. You have to pay only when you use any bundled product, such as Cloudera."
  • "We are using the free version of the solution."
  • "Apache Spark is not too cheap. You have to pay for hardware and Cloudera licenses. Of course, there is a solution with open source without Cloudera."
  • "Apache Spark is an expensive solution."
  • "Spark is an open-source solution, so there are no licensing costs."
  • "On the cloud model can be expensive as it requires substantial resources for implementation, covering on-premises hardware, memory, and licensing."
  • "It is an open-source solution, it is free of charge."
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  • "When comparing with Oracle Sybase and SQL, it's cheaper. It's not expensive."
  • "The price could be better for the product."
  • "I haven't bought a license for this solution. I'm only using the Apache license version."
  • "Cloudera requires a license to use."
  • "Cloudera Distribution for Hadoop is expensive, with support costs involved."
  • "I wouldn't recommend CDH to others because of its high cost."
  • "The price is very high. The solution is expensive."
  • "The solution is expensive."
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    Questions from the Community
    Top Answer:We use Spark to process data from different data sources.
    Top Answer:In data analysis, you need to take real-time data from different data sources. You need to process this in a subsecond, and do the transformation in a subsecond
    Top Answer:The tool can be deployed using different container technologies, which makes it very scalable.
    Top Answer:The tool is expensive. Overall, it's not a cheap software tool, and that is why only large enterprises who are mature enough and have an architecture that is complex enough opt for Cloudera, as its… more »
    Top Answer:The tool's ability to be deployed on a cloud model is an area of concern where improvements are required. The tool works very well when deployed on an on-premises model. The deployment on a cloud… more »
    Ranking
    1st
    out of 22 in Hadoop
    Views
    2,498
    Comparisons
    1,884
    Reviews
    25
    Average Words per Review
    432
    Rating
    8.7
    2nd
    out of 22 in Hadoop
    Views
    2,959
    Comparisons
    2,278
    Reviews
    14
    Average Words per Review
    409
    Rating
    8.1
    Comparisons
    Learn More
    Overview

    Spark provides programmers with an application programming interface centered on a data structure called the resilient distributed dataset (RDD), a read-only multiset of data items distributed over a cluster of machines, that is maintained in a fault-tolerant way. It was developed in response to limitations in the MapReduce cluster computing paradigm, which forces a particular linear dataflowstructure on distributed programs: MapReduce programs read input data from disk, map a function across the data, reduce the results of the map, and store reduction results on disk. Spark's RDDs function as a working set for distributed programs that offers a (deliberately) restricted form of distributed shared memory

    Cloudera Distribution for Hadoop is the world's most complete, tested, and popular distribution of Apache Hadoop and related projects. CDH is 100% Apache-licensed open source and is the only Hadoop solution to offer unified batch processing, interactive SQL, and interactive search, and role-based access controls. More enterprises have downloaded CDH than all other such distributions combined.
    Sample Customers
    NASA JPL, UC Berkeley AMPLab, Amazon, eBay, Yahoo!, UC Santa Cruz, TripAdvisor, Taboola, Agile Lab, Art.com, Baidu, Alibaba Taobao, EURECOM, Hitachi Solutions
    37signals, Adconion,adgooroo, Aggregate Knowledge, AMD, Apollo Group, Blackberry, Box, BT, CSC
    Top Industries
    REVIEWERS
    Computer Software Company30%
    Financial Services Firm15%
    University9%
    Marketing Services Firm6%
    VISITORS READING REVIEWS
    Financial Services Firm24%
    Computer Software Company13%
    Manufacturing Company7%
    Comms Service Provider6%
    REVIEWERS
    Financial Services Firm25%
    Computer Software Company21%
    Insurance Company14%
    Comms Service Provider11%
    VISITORS READING REVIEWS
    Financial Services Firm22%
    Computer Software Company16%
    Educational Organization9%
    Manufacturing Company8%
    Company Size
    REVIEWERS
    Small Business40%
    Midsize Enterprise19%
    Large Enterprise40%
    VISITORS READING REVIEWS
    Small Business17%
    Midsize Enterprise12%
    Large Enterprise71%
    REVIEWERS
    Small Business28%
    Midsize Enterprise17%
    Large Enterprise55%
    VISITORS READING REVIEWS
    Small Business16%
    Midsize Enterprise9%
    Large Enterprise75%
    Buyer's Guide
    Apache Spark vs. Cloudera Distribution for Hadoop
    March 2024
    Find out what your peers are saying about Apache Spark vs. Cloudera Distribution for Hadoop and other solutions. Updated: March 2024.
    768,578 professionals have used our research since 2012.

    Apache Spark is ranked 1st in Hadoop with 60 reviews while Cloudera Distribution for Hadoop is ranked 2nd in Hadoop with 47 reviews. Apache Spark is rated 8.4, while Cloudera Distribution for Hadoop is rated 8.0. The top reviewer of Apache Spark writes "Reliable, able to expand, and handle large amounts of data well". On the other hand, the top reviewer of Cloudera Distribution for Hadoop writes "Good end-to-end security features and we like that it's cloud independent". Apache Spark is most compared with Spring Boot, AWS Batch, Spark SQL, SAP HANA and AWS Lambda, whereas Cloudera Distribution for Hadoop is most compared with Amazon EMR, HPE Ezmeral Data Fabric, MongoDB, Cassandra and InfluxDB. See our Apache Spark vs. Cloudera Distribution for Hadoop report.

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    We monitor all Hadoop reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.