We performed a comparison between Apache Hadoop and Microsoft Analytics Platform System 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."It's open-source, so it's very cost-effective."
"The ability to add multiple nodes without any restriction is the solution's most valuable aspect."
"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."
"Apache Hadoop can manage large amounts and volumes of data with relative ease, which is a feature that is beneficial."
"Hadoop is designed to be scalable, so I don't think that it has limitations in regards to scalability."
"What comes with the standard setup is what we mostly use, but Ambari is the most important."
"The most valuable features are powerful tools for ingestion, as data is in multiple systems."
"Its integration is Hadoop's best feature because that allows us to support different tools in a big data platform."
"I like that it's integrated with other Azure products."
"Microsoft Analytics Platform System's most valuable feature is its ecosystems and seamless integration with other Microsoft reporting platforms and databases."
"The Cube Solution is quite different when compared to the rest of the competition and has unique functionality for advanced analytics."
"We leverage its capabilities for many applications. We can integrate with our databases, like Oracle, MySQL, or any other, using Microsoft Integration Services."
"It is closely integrated with other products in the MS portfolio."
"This solution will connect to any database, you can combine databases, and you can create a cube or tabular model."
"Helps our customers to discover trends, which provides useful information based on their business."
"This is a well-integrated solution and that integration empowers results."
"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 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 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 integration with Apache Hadoop with lots of different techniques within your business can be a challenge."
"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."
"In the next release, I would like to see Hive more responsive for smaller queries and to reduce the latency."
"General installation/dependency issues were there, but were not a major, complex issue. While migrating data from MySQL to Hive, things are a little challenging, but we were able to get through that with support from forums and a little trial and error."
"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."
"The pricing model needs to be improved."
"Hybrid environments are complex to manage."
"Releases of new products and functionality is never accompanied by associated documentation, training and resources that adequately explain the release."
"The flexibility of this solution needs to be improved because you cannot make changes at every one of the different steps."
"I think the biggest problem with the product is that it does a data ingest model, which is very expensive."
"Machine learning and artificial intelligence capabilities need to be more friendly for beginning users."
"Functionality needs to be more up-to-date with competing products."
"We need better real-time analytics capabilities. It's a bit challenging for us."
More Microsoft Analytics Platform System Pricing and Cost Advice →
Apache Hadoop is ranked 6th in Data Warehouse with 34 reviews while Microsoft Analytics Platform System is ranked 18th in Data Warehouse with 9 reviews. Apache Hadoop is rated 7.8, while Microsoft Analytics Platform System is rated 6.6. 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 Microsoft Analytics Platform System writes "Offers smooth data integration between systems, but requires better real-time analytics capabilities". Apache Hadoop is most compared with Azure Data Factory, Microsoft Azure Synapse Analytics, Oracle Exadata, Snowflake and Teradata, whereas Microsoft Analytics Platform System is most compared with Microsoft Azure Synapse Analytics and IBM Netezza Performance Server. See our Apache Hadoop vs. Microsoft Analytics Platform System 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.
