We performed a comparison between Apache Hadoop and VMware Tanzu Data Services 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 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."
"Its integration is Hadoop's best feature because that allows us to support different tools in a big data platform."
"It's open-source, so it's very cost-effective."
"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."
"The most valuable feature is scalability and the possibility to work with major information and open source capability."
"The tool's stability is good."
"I liked that Apache Hadoop was powerful, had a lot of tools, and the fact that it was free and community-developed."
"It's primarily open source. You can handle huge data volumes and create your own views, workflows, and tables. I can also use it for real-time data streaming."
"Some of the most valuable features are publish and subscribe, fanout, and queues."
"The most valuable feature is asynchronous calls, which are easy to configure."
"The stability of this solution was very good."
"Scalability is simple because it's an MPP database. If you need more processing power or you need more storage, you just add a few more nodes in the cluster. It works on common commodity hardware. You can use any type of server. You don't need to have proprietary hardware. It's fairly flexible."
"With VMware Tanzu Greenplum, one can make a huge database table and analyze the queries by adding in the SQL command. Some hint or command for the query goes over the multi-parallel execution."
"RabbitMQ provides access to SDKs for development and the ability to raise and log tickets if we encounter issues. We can integrate RabbitMQ using various languages like Java or Python using the provided SDKs."
"After creating a RabbitMQ service, they provide you with a sort of web management dashboard."
"The message routing is the most valuable feature. It is effective and flexible."
"The solution is very expensive."
"The solution could use a better user interface. It needs a more effective GUI in order to create a better user environment."
"The solution needs a better tutorial. There are only documents available currently. There's a lot of YouTube videos available. However, in terms of learning, we didn't have great success trying to learn that way. There needs to be better self-paced learning."
"I would like to see more direct integration of visualization applications."
"Real-time data processing is weak. This solution is very difficult to run and implement."
"The stability of the solution needs improvement."
"The upgrade path should be improved because it is not as easy as it should be."
"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."
"I would like to see the performance of the administration portal improved and additional messaging protocols."
"The product needs to focus on offering more use case documentation because browsing the internet to find it can be a process filled with struggles."
"VMware RabbitMQ's configuration process could be easier to understand."
"It doesn't have any GUI-based monitoring tools."
"I’d like this dashboard to use web sockets, so it would actually be in real time. It would slightly increase debugging, etc."
"The availability could be better."
"They need to enhance integration with other Big Data products... to integrate with Big Data platforms, and to open a bi-directional connection between Greenplum and Big Data."
"The product has to improve the crisis management, especially in memory issues."
Apache Hadoop is ranked 6th in Data Warehouse with 34 reviews while VMware Tanzu Data Services is ranked 5th in Data Warehouse with 81 reviews. Apache Hadoop is rated 7.8, while VMware Tanzu Data Services is rated 8.0. 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 VMware Tanzu Data Services writes "Reliable queueing functionality and versatile tool that can be used with any programming languages ". Apache Hadoop is most compared with Azure Data Factory, Microsoft Azure Synapse Analytics, Oracle Exadata, Snowflake and Dremio, whereas VMware Tanzu Data Services is most compared with IBM MQ, Anypoint MQ, Apache Kafka and Red Hat AMQ. See our Apache Hadoop vs. VMware Tanzu Data Services 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.
