We performed a comparison between Apache Hadoop and Microsoft Parallel Data 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."The most valuable feature is scalability and the possibility to work with major information and open source capability."
"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 most important feature is its ability to handle large volumes. Some of our customers have really large volumes, and it is capable of handling their data in terms of the core volume and daily incremental volume. So, its processing power and speed are most valuable."
"The scalability of Apache Hadoop is very good."
"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 feature is the database."
"Its integration is Hadoop's best feature because that allows us to support different tools in a big data platform."
"It's good for storing historical data and handling analytics on a huge amount of data."
"It is not a pricey product compared to other data warehouse solutions."
"It is a very stable database."
"It is a stable solution...It is a scalable solution."
"Microsoft Parallel Data Warehouse integrates beautifully with other Microsoft ecosystem products."
"The solution's integration is good."
"One of the most important features is the ease of using MS SQL."
"It has allowed fast daily loads and analysis of millions of rows of data, which eventually moved to near real-time."
"Data collection and reporting are valuable features of the solution."
"The solution is very expensive."
"It could be more user-friendly."
"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is probably the only feature we can improve a little bit because the terminal and coding screen on Hadoop is a little outdated, and it looks like the old C++ bio screen.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."
"It needs better user interface (UI) functionalities."
"I think more of the solution needs to be focused around the panel processing and retrieval of data."
"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."
"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."
"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."
"I would like the tool to support different operating systems."
"The reporting for certain types of data needs to be improved."
"It could offer more development across the solution."
"The solution is expensive and has room for improvement."
"More tools to help designers should be included."
"If the database is large with a lot of columns then it is difficult to clean the data."
"In the future I would love to see a slightly better automation engine, just for the data integration layer, to make it slightly easier for end-users or junior developers to get involved in incremental updating."
"They need to incorporate a machine learning engine."
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Apache Hadoop is ranked 5th in Data Warehouse with 32 reviews while Microsoft Parallel Data Warehouse is ranked 8th in Data Warehouse with 32 reviews. Apache Hadoop is rated 7.8, while Microsoft Parallel Data 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 Microsoft Parallel Data Warehouse writes "An easy to setup tool that allows its users to write stored procedure, making it a scalable product". Apache Hadoop is most compared with Azure Data Factory, Microsoft Azure Synapse Analytics, Oracle Exadata, Snowflake and Teradata, whereas Microsoft Parallel Data Warehouse is most compared with Microsoft Azure Synapse Analytics, Oracle Exadata, SAP BW4HANA, VMware Tanzu Greenplum and Snowflake. See our Apache Hadoop vs. Microsoft Parallel Data Warehouse report.
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