We performed a comparison between Amazon Redshift and Apache Hadoop based on real PeerSpot user reviews.
Find out in this report how the two Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The most valuable feature of Amazon Redshift is its ability to handle really large sets of data."
"If the analyst knows SQL, which is comfortable and easy to use to go between all of these tool stacks, I think it's reliable. It's a secure and reliable data warehouse."
"I have primarily used the Redshift Spectrum feature and found it most valuable."
"I like the cost-benefit ratio, meaning that it is as easy to use as it is powerful and well-performing."
"The most valuable feature of Redshift is its cluster."
"The most valuable feature is that the solution is fully embedded in the AWS stack."
"Though Amazon Redshift is good, it depends on what kind of business you're trying to do, what type of analytics you need, and how much data you have."
"In terms of valuable features, I like the columnar storage that Redshift provides. The storage is one of the key features that we're looking for. Also, the data updates and the latency between the data-refreshes."
"It's open-source, so it's very cost-effective."
"Initially, with RDBMS alone, we had a lot of work and few servers running on-premise and on cloud for the PoC and incubation. With the use of Hadoop and ecosystem components and tools, and managing it in Amazon EC2, we have created a Big Data "lab" which helps us to centralize all our work and solutions into a single repository. This has cut down the time in terms of maintenance, development and, especially, data processing challenges."
"The most valuable features are powerful tools for ingestion, as data is in multiple systems."
"Two valuable features are its scalability and parallel processing. There are jobs that cannot be done unless you have massively parallel processing."
"The ability to add multiple nodes without any restriction is the solution's most valuable aspect."
"Data ingestion: It has rapid speed, if Apache Accumulo is used."
"Hadoop is extensible — it's elastic."
"I liked that Apache Hadoop was powerful, had a lot of tools, and the fact that it was free and community-developed."
"In the next release, a pivot function would be a big help. It could save a lot of time creating a query or process to handle operations."
"Pricing is one of the things that it could improve. It should be more competitive."
"Amazon should provide more cloud-native tools that can integrate with Redshift like Microsoft's development tools for Azure."
"This solution lacks integration with non-AWS sources."
"Redshift's GUI could be more user-friendly. It's easier to perform queries and all that stuff in Azure Synapse Analytics."
"The OLAP slide and dice features need to be improved."
"Should be made available across zones, like other Multi-AZ solutions."
"It takes a lot of time to ingest and update the data."
"The main thing is the lack of community support. If you want to implement a new API or create a new file system, you won't find easy support."
"There is a lack of virtualization and presentation layers, so you can't take it and implement it like a radio solution."
"The stability of the solution needs improvement."
"What could be improved in Apache Hadoop is its user-friendliness. It's not that user-friendly, but maybe it's because I'm new to it. Sometimes it feels so tough to use, but it could be because of two aspects: one is my incompetency, for example, I don't know about all the features of Apache Hadoop, or maybe it's because of the limitations of the platform. For example, my team is maintaining the business glossary in Apache Atlas, but if you want to change any settings at the GUI level, an advanced level of coding or programming needs to be done in the back end, so it's not user-friendly."
"In certain cases, the configurations for dealing with data skewness do not make any sense."
"The price could be better. I think we would use it more, but the company didn't want to pay for it. Hortonworks doesn't exist anymore, and Cloudera killed the free version of Hadoop."
"Real-time data processing is weak. This solution is very difficult to run and implement."
"I think more of the solution needs to be focused around the panel processing and retrieval of data."
Amazon Redshift is ranked 4th in Cloud Data Warehouse with 58 reviews while Apache Hadoop is ranked 5th in Data Warehouse with 32 reviews. Amazon Redshift is rated 7.8, while Apache Hadoop is rated 7.8. The top reviewer of Amazon Redshift writes "Provides one place where we can store data, and allows us to easily connect to other services with AWS". On the other hand, the top reviewer of Apache Hadoop writes "A file system for data collection that contains needed information and files". Amazon Redshift is most compared with AWS Lake Formation, Snowflake, Teradata and Vertica, whereas Apache Hadoop is most compared with Azure Data Factory, Microsoft Azure Synapse Analytics, Oracle Exadata, Snowflake and Vertica. See our Amazon Redshift vs. Apache Hadoop report.
See our list of best Data Warehouse vendors and best Cloud Data Warehouse vendors.
We monitor all Data Warehouse 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.
