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 solution has very competitive pricing."
"The ability to reload data multiple times at different times."
"The most valuable feature is that the solution is fully embedded in the AWS stack."
"The processing of data is very fast."
"The solution is scalable. It handles different loads very well."
"It is quite simple to use and there are no issues with creating the tables."
"Setup is easy. It's a fast solution with machine learning features, good integration, and a good API."
"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."
"The solution is easy to expand. We haven't seen any issues with it in that sense. We've added 10 servers, and we've added two nodes. We've been expanding since we started using it since we started out so small. Companies that need to scale shouldn't have a problem doing so."
"The most valuable features are the ability to process the machine data at a high speed, and to add structure to our data so that we can generate relevant analytics."
"Since both Apache Hadoop and Amazon EC2 are elastic in nature, we can scale and expand on demand for a specific PoC, and scale down when it's done."
"The tool's stability is good."
"What I like about Apache Hadoop is that it's for big data, in particular big data analysis, and it's the easier solution. I like the data processing feature for AI/ML use cases the most because some solutions allow me to collect data from relational databases, while Hadoop provides me with more options for newer technologies."
"Data ingestion: It has rapid speed, if Apache Accumulo is used."
"The most valuable feature is the database."
"The most valuable feature is scalability and the possibility to work with major information and open source capability."
"The product could be improved by making it more flexible."
"This solution lacks integration with non-AWS sources."
"One area where Amazon Redshift could improve is in adopting the compute-separate, data-separate architecture, which Delta, Snowflake are adopting, and a few others in the cloud data warehouse spectrum."
"For people who struggle with IAM or role-based management, the setup isn't easy."
"The speed of the solution and its portability needs improvement."
"We recently moved from the DC2 cluster to the RA3 cluster, which is a different node type and we are finding some issues with the RA3 cluster regarding connection and processing. There is room for improvement in this area. We are in talks with AWS regarding the connection issues."
"The initial setup is a complex process, especially for someone who is not familiar with nodes and configuring terms like RPUs."
"Amazon should provide more cloud-native tools that can integrate with Redshift like Microsoft's development tools for Azure."
"The key shortcoming is its inability to handle queries when there is insufficient memory. This limitation can be bypassed by processing the data in chunks."
"The solution could use a better user interface. It needs a more effective GUI in order to create a better user environment."
"I think more of the solution needs to be focused around the panel processing and retrieval of data."
"The stability of the solution needs improvement."
"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."
"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."
"It could be more user-friendly."
"The solution is not easy to use. The solution should be easy to use and suitable for almost any case connected with the use of big data or working with large amounts 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.
