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."The most crucial feature for us is the streaming capability. It serves as a fundamental aspect that allows us to exert control over our operations."
"The most valuable feature of Apache Spark is its memory processing because it processes data over RAM rather than disk, which is much more efficient and fast."
"The fault tolerant feature is provided."
"DataFrame: Spark SQL gives the leverage to create applications more easily and with less coding effort."
"It's easy to prepare parallelism in Spark, run the solution with specific parameters, and get good performance."
"Apache Spark can do large volume interactive data analysis."
"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 feature is the SQL tool. It enables us to create a database and publish it."
"We had a data warehouse before all the data. We can process a lot more data structures."
"It is helpful to gather and process data."
"We also really like the Cloudera community. You can have any question and will have your answer within a few hours."
"Cloudera is a very manageable solution with good support."
"The data science aspect of the solution is valuable."
"The solution is reliable and stable, it fits our requirements."
"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."
"Customer service and support were able to fix whatever the issue was."
"They could improve the issues related to programming language for the platform."
"The logging for the observability platform could be better."
"Technical expertise from an engineer is required to deploy and run high-tech tools, like Informatica, on Apache Spark, making it an area where improvements are required to make the process easier for users."
"Apache Spark should add some resource management improvements to the algorithms."
"The management tools could use improvement. Some of the debugging tools need some work as well. They need to be more descriptive."
"Apache Spark is very difficult to use. It would require a data engineer. It is not available for every engineer today because they need to understand the different concepts of Spark, which is very, very difficult and it is not easy to learn."
"Apart from the restrictions that come with its in-memory implementation. It has been improved significantly up to version 3.0, which is currently in use."
"We are building our own queries on Spark, and it can be improved in terms of query handling."
"While the deployed product is generally functional, there are instances where it presents difficulties."
"The Cloudera training has deteriorated significantly."
"Cloudera's support is extremely bad and cannot be relied on."
"The solution is not fit for on-premise distributions."
"Cloudera Distribution for Hadoop is not always completely stable in some cases, which can be a concern for big data solutions."
"There are multiple bugs when we update."
"The user infrastructure and user interface needs to be improved, as well as the performance. The GUI needs to be better."
"Cloudera Distribution for Hadoop has a limited feature list and a lot of costs involved."
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.
