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."This service can merge and integrate well with all databases."
"The initial setup of this solution is straightforward."
"It allows for the storage of huge amounts of data."
"You can copy JSON to the column and have it analyzed using simple functions."
"Easy to build out our snowflake design and load data."
"The stability of Amazon Redshift is good."
"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."
"The most valuable feature is its scalability."
"One valuable feature is that we can download data."
"We selected Apache Hadoop because it is not dependent on third-party vendors."
"It is a file system for data collection. There are nodes in this cluster that contain all the information, directories, and other files. The nodes are based on the MySQL database."
"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."
"The most valuable feature is the database."
"The best thing about this solution is that it is very powerful and very cheap."
"Apache Hadoop is crucial in projects that save and retrieve data daily. Its valuable features are scalability and stability. It is easy to integrate with the existing infrastructure."
"Most valuable features are HDFS and Kafka: Ingestion of huge volumes and variety of unstructured/semi-structured data is feasible, and it helps us to quickly onboard a new Big Data analytics prospect."
"It lacks a few features which can be very useful, such as stored procedures"
"There is some missing functionality and sometimes it's so difficult to work in. We need to convert these functionalities using VACUUM inside Amazon Redshift and then it causes some complexity."
"The initial setup is a complex process, especially for someone who is not familiar with nodes and configuring terms like RPUs."
"It takes a lot of time to ingest and update the data."
"The product must become a bit more serverless."
"This solution lacks integration with non-AWS sources."
"The speed of the solution and its portability needs improvement."
"Infinite storage is available in Snowflake and is not available in Redshift."
"The solution could use a better user interface. It needs a more effective GUI in order to create a better user environment."
"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."
"From the Apache perspective or the open-source community, they need to add more capabilities to make life easier from a configuration and deployment perspective."
"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."
"It would be good to have more advanced analytics tools."
"I would like to see more direct integration of visualization applications."
"It would be helpful to have more information on how to best apply this solution to smaller organizations, with less data, and grow the data lake."
"Real-time data processing is weak. This solution is very difficult to run and implement."
Amazon Redshift is ranked 4th in Cloud Data Warehouse with 61 reviews while Apache Hadoop is ranked 6th in Data Warehouse with 34 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 "Handles huge data volumes and create your own workflows and tables but you need to have deeper knowledge". Amazon Redshift is most compared with Teradata, Vertica, Snowflake, Microsoft Azure Synapse Analytics and AWS Lake Formation, whereas Apache Hadoop is most compared with Azure Data Factory, Microsoft Azure Synapse Analytics, Oracle Exadata, Snowflake and Oracle Big Data Appliance. 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.
