Hadoop is an open source software from Apache, supporting distributed processing and data storage. Hadoop is popular for its scalability, reliability, and functionality available across commoditized hardware.
N/A
Azure HDInsight
Score 4.0 out of 10
N/A
HDInsight is an implementation of the Apache Hadoop technology stack on the Microsoft Azure cloud platform: It is based on the Hortonworks Hadoop distribution. Microsoft Azure HDInsight includes implementations of Apache Spark, HBase, Storm, Pig, Hive, Sqoop, Oozie, Ambari, etc. It also integrates with with business intelligence (BI) tools such as Power BI, Excel, SQL Server Analysis Services, and SQL Server Reporting Services.
Apache Hadoop (and its subsequent add-ons) are well-suited to larger, unstructured data flows, such as aggregation of web traffic or advertising. Geospatial algorithms and their outputs are well-suited for this kind of aggregation as structuring that data is challenging, but leaving it unstructured and performing queries as-needed is a better fit for most business models. With the advent of data science, I would expect Hadoop fits a LOT of their initial outputs quite well.
If you want to save costs and just pay for what you use, I highly recommend it. It will help you also to work with data for your reports and analytics. on the other hand I think it could be the subscription you have but high volume of data make it slow but not so much. anyway I think it's really good because it's from Microsoft which always is friendly to use it as all the suit they have.
Shows live changes in analytics. Shows you how social media is working for us. Since we promote weekly events this is something that we really need to pay attention to.
Azure in itself is very user-friendly, HDInsight is a great addition. For our purposes, we definitely also utilized the power query to translate data to Excel.
Hadoop is a batch oriented processing framework, it lacks real time or stream processing.
Hadoop's HDFS file system is not a POSIX compliant file system and does not work well with small files, especially smaller than the default block size.
Hadoop cannot be used for running interactive jobs or analytics.
Hadoop is organization-independent and can be used for various purposes ranging from archiving to reporting and can make use of economic, commodity hardware. There is also a lot of saving in terms of licensing costs - since most of the Hadoop ecosystem is available as open-source and is free
Great! Hadoop has an easy to use interface that mimics most other data warehouses. You can access your data via SQL and have it display in a terminal before exporting it to your business intelligence platform of choice. Of course, for smaller data sets, you can also export it to Microsoft Excel.
Azure HDInsight is usable on the top of Azure Data Lake and gives us the benefit of analyzing large scale data workload in Hadoop. Usability and support from Microsoft are outstanding.
We went with a third party for support, i.e., consultant. Had we gone with Azure or Cloudera, we would have obtained support directly from the vendor. my rating is more on the third party we selected and doesn't reflect the overall support available for Hadoop. I think we could have done better in our selection process, however, we were trying to use an already approved vendor within our organization. There is plenty of self-help available for Hadoop online.
Inexpert, isolated teams... not good for support an excessively complex platform. Lots of weeks or months for a complex problem troubleshoot. Many time lost stuck on MindTree, before the case was finally escalated with Microsoft!
I feel that this is a highly reliable and scalable solution computing technology that is highly capable of processing large data sets across multiple servers and thousands of machines in a well-defined and distributed manner. Apache Hadoop can automatically scale up the number of servers and machines that are needed to process, store, and analyze data sets. It also handles explosions in data with big data technology. Apache Hadoop is good at handling all node failures as well.
Many times you just need spark performing fast and cheap. Azure HDInsight Includes lots of features and not required software. Also its libraries and runtime versions are pritty old. But, what is great Is you don't need to have an expert in your team and things -when work- performs always in the exact same way. Also, as I mentioned, for a starter that's a great ROI.
As it was open source makes it popular choice for handling large chuck of datasets
It was free earlier but now it’s licensed but still enterprise is a fine tuned version which makes it easier for new users and administrators to use it
Our investment is worth every single penny.
Initial cost is more as you might need to hire administrators to setup the cluster and make them in scalable. But once done it’s pretty easy
