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."Two valuable features are its scalability and parallel processing. There are jobs that cannot be done unless you have massively parallel processing."
"Apache Hadoop can manage large amounts and volumes of data with relative ease, which is a feature that is beneficial."
"The most valuable feature is scalability and the possibility to work with major information and open source capability."
"High throughput and low latency. We start with data mashing on Hive and finally use this for KPI visualization."
"I liked that Apache Hadoop was powerful, had a lot of tools, and the fact that it was free and community-developed."
"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."
"Hadoop File System is compatible with almost all the query engines."
"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."
"The analytics engine is not bad at forecasting predictions."
"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."
"The solution is stable."
"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."
"Some of the best features are stored procedures, parallelism, and different indexing strategies."
"Provides good security and reliability."
"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."
"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."
"There is a lack of virtualization and presentation layers, so you can't take it and implement it like a radio solution."
"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 good to have more advanced analytics tools."
"Hadoop's security could be better."
"In the next release, I would like to see Hive more responsive for smaller queries and to reduce the latency."
"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."
"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."
"There were some initial challenges with IBM Db2 Warehouse about eight months ago when I worked in this environment. When I coordinated with IBM support, they mentioned that the memory was insufficient for our needs. Our business environment required significantly more memory than the previous cluster could provide. Consequently, we have worked closely with on-site IBM technical personnel to address this issue."
"In terms of improvement, IBM Db2 Warehouse should be more scalable."
"There should be more material available for training and training should be free."
"IBM Db2 Warehouse needs to improve its interface."
"The areas of the solution that is needing the most improvement are separating compute from storage, elasticity, which means scaling up and then retracting."
"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 33 reviews while IBM Db2 Warehouse is ranked 13th in Data Warehouse with 9 reviews. Apache Hadoop is rated 7.8, while IBM Db2 Warehouse is rated 7.8. 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". 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 and Snowflake, whereas IBM Db2 Warehouse is most compared with Oracle Exadata, Snowflake, Amazon Redshift, Teradata and IBM Db2 Warehouse on Cloud. See our Apache Hadoop vs. IBM Db2 Warehouse report.
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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.
