We performed a comparison between Apache Hadoop and Microsoft Azure Synapse Analytics based on our users’ reviews in four categories. After reading all of the collected data, you can find our conclusion below.
Comparison Results: Synapse has a slight edge in this comparison. According to its users, it is more user-friendly and less expensive than Hadoop.
"One valuable feature is that we can download data."
"The tool's stability is good."
"Apache Hadoop can manage large amounts and volumes of data with relative ease, which is a feature that is beneficial."
"What comes with the standard setup is what we mostly use, but Ambari is the most important."
"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."
"It's open-source, so it's very cost-effective."
"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."
"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."
"Overall deployment and integration is pretty fast."
"Our primary use case is for gathering data and analytics. We provide insights into vehicle data. We gather millions of records per second and we have various millions of vehicles running across."
"The speed is great and the architecture is excellent."
"They are available on the Cloud, and the platform is very intuitive."
"I like how Microsoft Azure Synapse Analytics integrates with other Microsoft solutions."
"The most valuable features of Microsoft Azure Synapse Analytics are the interface and the agility of the on-cloud platform."
"The solution's best feature is its predictive analytics."
"Technical support is okay in terms of the help they provide."
"We would like to have more dynamics in merging this machine data with other internal data to make more meaning out of it."
"Since it is an open-source product, there won't be much support."
"I think more of the solution needs to be focused around the panel processing and retrieval of data."
"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."
"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."
"The solution could use a better user interface. It needs a more effective GUI in order to create a better user environment."
"The integration with Apache Hadoop with lots of different techniques within your business can be a challenge."
"There is a limit on the number of concurrent queries to around 125 for Azure Synapse."
"Microsoft Azure Synapse Analytics's pricing could be reduced."
"I am pretty sure that there are areas that need improvement but I just can think of them off the top of my head."
"It's a complicated product."
"It's stable, but its stability could be better. However, we understand that it's in production, and new features are getting added and upgraded, so you do get hiccups sometimes."
"Non-structured data is unavailable with this product."
"It needs strong support for social media, internet data, and native support for NoSQL."
"It would be of interest to improve things like the web service integration and availability in terms of being easy to create internal web services in the database."
More Microsoft Azure Synapse Analytics Pricing and Cost Advice →
Apache Hadoop is ranked 5th in Data Warehouse with 33 reviews while Microsoft Azure Synapse Analytics is ranked 2nd in Cloud Data Warehouse with 86 reviews. Apache Hadoop is rated 7.8, while Microsoft Azure Synapse Analytics 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 Microsoft Azure Synapse Analytics writes "No competitors provide the entire solution to one place ". Apache Hadoop is most compared with Azure Data Factory, Oracle Exadata, Snowflake, Teradata and BigQuery, whereas Microsoft Azure Synapse Analytics is most compared with Azure Data Factory, SAP BW4HANA, Snowflake, Oracle Autonomous Data Warehouse and AWS Lake Formation. See our Apache Hadoop vs. Microsoft Azure Synapse Analytics report.
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