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."I like that it can handle multiple tasks parallelly. I also like the automation feature. JavaScript also helps with the parallel streaming of the library."
"The product’s most valuable features are lazy evaluation and workload distribution."
"The tool's most valuable feature is its speed and efficiency. It's much faster than other tools and excels in parallel data processing. Unlike tools like Python or JavaScript, which may struggle with parallel processing, it allows us to handle large volumes of data with more power easily."
"The fault tolerant feature is provided."
"Apache Spark provides a very high-quality implementation of distributed data processing."
"DataFrame: Spark SQL gives the leverage to create applications more easily and with less coding effort."
"Spark helps us reduce startup time for our customers and gives a very high ROI in the medium term."
"There's a lot of functionality."
"The data science aspect of the solution is valuable."
"The solution's most valuable feature is the enterprise data platform."
"The solution is reliable and stable, it fits our requirements."
"The main advantage is the storage is less expensive."
"The file system is a valuable feature."
"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."
"With a cluster available, you can manage the security layer using the shared SDX - it provides flexibility."
"Customer service and support were able to fix whatever the issue was."
"Include more machine learning algorithms and the ability to handle streaming of data versus micro batch processing."
"Apache Spark provides very good performance The tuning phase is still tricky."
"We use big data manager but we cannot use it as conditional data so whenever we're trying to fetch the data, it takes a bit of time."
"The solution’s integration with other platforms should be improved."
"I would like to see integration with data science platforms to optimize the processing capability for these tasks."
"At times during the deployment process, the tool goes down, making it look less robust. To take care of the issues in the deployment process, users need to do manual interventions occasionally."
"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."
"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 price of this solution could be lowered."
"The competitors provide better functionalities."
"The procedure for operations could be simplified."
"The pricing needs to improve."
"They should focus on upgrading their technical capabilities in the market."
"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 solution does not support multiple languages very well and this means users need to create work-arounds to implement some solutions."
"It would be useful if Cloudera had more tools like SQL Engines that offer the traditional relational database. We have to do a lot of work preparing the data outside Cloudera before getting it into the platform."
More Cloudera Distribution for Hadoop Pricing and Cost Advice →
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.
See our list of best Hadoop vendors.
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.
