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.
"Hadoop File System is compatible with almost all the query engines."
"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 ability to add multiple nodes without any restriction is the solution's most valuable aspect."
"Hadoop is designed to be scalable, so I don't think that it has limitations in regards to scalability."
"High throughput and low latency. We start with data mashing on Hive and finally use this for KPI visualization."
"Its integration is Hadoop's best feature because that allows us to support different tools in a big data platform."
"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."
"Technical support is okay in terms of the help they provide."
"I like SQL post, which is for storage and distributed computing. Another good feature is the copy activity."
"They are very reliable and cost-effective."
"The whole solution is interesting for us."
"The features we've found most valuable for data warehouses is extracting data, SSIS packages, and the DBs."
"I think the most valuable component is that pipelines are built into it and then the feature that you can mirror a cosmos BB for analytics."
"The speed is great and the architecture is excellent."
"We have found that it is easy to develop and to do the analytics in the modules of data."
"The stability of the solution needs improvement."
"Since it is an open-source product, there won't be much support."
"There is a lack of virtualization and presentation layers, so you can't take it and implement it like a radio solution."
"The load optimization capabilities of the product are an area of concern where improvements are required."
"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."
"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."
"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."
"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."
"The cost of the solution has room for improvement."
"The solution should offer a serverless model like Snowflake."
"It could be beneficial to focus on integration with various data sources and similar enhancements."
"It needs strong support for social media, internet data, and native support for NoSQL."
"Microsoft Azure Synapse Analytics can improve by adding more flexibility to the reports. Having more visible structures based on the area, region and country would be beneficial."
"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."
"The only issue that we have run into with the solutions performance is with regards to concurrency."
"We encountered data processing and transformation issues while working with Apache Spark languages for the product."
More Microsoft Azure Synapse Analytics Pricing and Cost Advice →
Apache Hadoop is ranked 5th in Data Warehouse with 34 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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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.