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."We use Spark to process data from different data sources."
"The distribution of tasks, like the seamless map-reduce functionality, is quite impressive."
"Apache Spark can do large volume interactive data analysis."
"The features we find most valuable are the machine learning, data learning, and Spark Analytics."
"DataFrame: Spark SQL gives the leverage to create applications more easily and with less coding effort."
"We use it for ETL purposes as well as for implementing the full transformation pipelines."
"Its scalability and speed are very valuable. You can scale it a lot. It is a great technology for big data. It is definitely better than a lot of earlier warehouse or pipeline solutions, such as Informatica. Spark SQL is very compliant with normal SQL that we have been using over the years. This makes it easy to code in Spark. It is just like using normal SQL. You can use the APIs of Spark or you can directly write SQL code and run it. This is something that I feel is useful in Spark."
"It provides a scalable machine learning library."
"The most valuable feature is that I can use CDH for almost all use cases across all industries, including the financial sector, public sector, private retailers, and so on."
"It has the best proxy, security, and support features compared to open-source products."
"The solution is reliable and stable, it fits our requirements."
"In terms of scalability, if you have enough hardware you can scale out. Scalability doesn't have any issues."
"Cloudera is a very manageable solution with good support."
"With a cluster available, you can manage the security layer using the shared SDX - it provides flexibility."
"The product is completely secure."
"We had a data warehouse before all the data. We can process a lot more data structures."
"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."
"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."
"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."
"There were some problems related to the product's compatibility with a few Python libraries."
"Apache Spark provides very good performance The tuning phase is still tricky."
"When using Spark, users may need to write their own parallelization logic, which requires additional effort and expertise."
"I would like to see integration with data science platforms to optimize the processing capability for these tasks."
"It needs a new interface and a better way to get some data. In terms of writing our scripts, some processes could be faster."
"The competitors provide better functionalities."
"It could be faster and more user-friendly."
"Cloudera Distribution for Hadoop has a limited feature list and a lot of costs involved."
"Without the big data environment, we cannot store all of this data live. We have billions of records and terabytes of storage to be used. It's not an option actually for us to have a big data environment."
"There are better solutions out there that have more features than this one."
"They should focus on upgrading their technical capabilities in the market."
"The dashboard could be improved."
"The price of this solution could be lowered."
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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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