We performed a comparison between Apache Hadoop and IBM Db2 Warehouse 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."Hadoop is designed to be scalable, so I don't think that it has limitations in regards to scalability."
"The tool's stability is good."
"The performance is pretty good."
"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."
"As compared to Hive on MapReduce, Impala on MPP returns results of SQL queries in a fairly short amount of time, and is relatively fast when reading data into other platforms like R."
"The most valuable feature is scalability and the possibility to work with major information and open source capability."
"The most valuable feature is the database."
"The most valuable features are powerful tools for ingestion, as data is in multiple systems."
"Some of the best features are stored procedures, parallelism, and different indexing strategies."
"Provides good security and reliability."
"It can be mounted on the cloud, which is a huge plus. If the client, for example, starts small with on-premise deployment and then it rapidly needs to grow, we can transfer this to the cloud easily."
"I think it scales really well and as long as you take enough time to learn a little bit about it, it works really well."
"The standout feature of IBM Db2 Warehouse, which is particularly valuable for large enterprises, is its ability to handle big data."
"The analytics engine is not bad at forecasting predictions."
"Based on our needs, we would like to see a tool for data visualization and enhanced Ambari for management, plus a pre-built IoT hub/model. These would reduce our efforts and the time needed to prove to a customer that this will help them."
"It requires a great deal of learning curve to understand. The overall Hadoop ecosystem has a large number of sub-products. There is ZooKeeper, and there are a whole lot of other things that are connected. In many cases, their functionalities are overlapping, and for a newcomer or our clients, it is very difficult to decide which of them to buy and which of them they don't really need. They require a consulting organization for it, which is good for organizations such as ours because that's what we do, but it is not easy for the end customers to gain so much knowledge and optimally use it."
"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."
"The solution is very expensive."
"I mentioned it definitely, and this is probably the only feature we can improve a little bit because the terminal and coding screen on Hadoop is a little outdated, and it looks like the old C++ bio screen. If the UI and UX can be improved slightly, I believe it will go a long way toward increasing adoption and effectiveness."
"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."
"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."
"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."
"In terms of improvement, IBM Db2 Warehouse should be more scalable."
"The areas of the solution that is needing the most improvement are separating compute from storage, elasticity, which means scaling up and then retracting."
"There should be more material available for training and training should be free."
"The biggest problems we have is when the backup solution is failing or slow and we run out of log space, which has happened probably a couple of times in the last four years."
"Lacks sufficient documentation and particularly in Spanish."
"IBM Db2 Warehouse needs to improve its interface."
"The biggest challenge anyone could have with Db2 Warehouse is their references or online resources and documentation. They are very, very, very limited on the web."
Apache Hadoop is ranked 5th in Data Warehouse with 32 reviews while IBM Db2 Warehouse is ranked 14th in Data Warehouse with 8 reviews. Apache Hadoop is rated 7.8, while IBM Db2 Warehouse is rated 7.6. The top reviewer of Apache Hadoop writes "A file system for data collection that contains needed information and files". On the other hand, the top reviewer of IBM Db2 Warehouse writes "Useful for ETL process and has good documentation ". Apache Hadoop is most compared with Azure Data Factory, Microsoft Azure Synapse Analytics, Oracle Exadata, Snowflake and Dremio, whereas IBM Db2 Warehouse is most compared with Oracle Exadata, Snowflake, Amazon Redshift, IBM Db2 Warehouse on Cloud and BigQuery. See our Apache Hadoop vs. IBM Db2 Warehouse report.
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