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."With Spark, we parallelize our operations, efficiently accessing both historical and real-time data."
"With Hadoop-related technologies, we can distribute the workload with multiple commodity hardware."
"The product’s most valuable feature is the SQL tool. It enables us to create a database and publish it."
"We use it for ETL purposes as well as for implementing the full transformation pipelines."
"I found the solution stable. We haven't had any problems with it."
"The solution is scalable."
"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."
"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 features I find most valuable is that the solution is that it is easy to install and to work with. It starts with the installation and from there on the management is very simple and centralized."
"The data science aspect of the solution is valuable."
"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."
"It is helpful to gather and process data."
"The scalability of Cloudera Distribution for Hadoop is excellent."
"The solution is stable."
"The tool can be deployed using different container technologies, which makes it very scalable."
"CDH has a wide variety of proprietary tools that we use, like Impala. So from that perspective, it's quite useful as opposed to something open-source. We get a lot of value from Cloudera's proprietary tools."
"We are building our own queries on Spark, and it can be improved in terms of query handling."
"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."
"It requires overcoming a significant learning curve due to its robust and feature-rich nature."
"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."
"Stream processing needs to be developed more in Spark. I have used Flink previously. Flink is better than Spark at stream processing."
"The solution’s integration with other platforms should be improved."
"Include more machine learning algorithms and the ability to handle streaming of data versus micro batch processing."
"The management tools could use improvement. Some of the debugging tools need some work as well. They need to be more descriptive."
"While the deployed product is generally functional, there are instances where it presents difficulties."
"The solution does not support multiple languages very well and this means users need to create work-arounds to implement some solutions."
"There is a maximum of a one-gigabyte block size, which is an area of storage that can be improved upon."
"The governance aspect of the solution should be improved."
"This is a very expensive solution."
"I would like to see an improvement in how the solution helps me to handle the whole cluster."
"The competitors provide better functionalities."
"The areas of improvement depend on the scale of the project. For banking customers, security features and an essential budget for commercial licenses would be the top priority. Data regulation could be the most crucial for a project with extensive data or an extra use case."
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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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