Apache Flume vs. Azure HDInsight

Apache Flume is well suited in small batch and near real time processing projects, taking data from one point to another with local processing (I mean not external enrichment).
Filtering, transforming and multiple push destinations are common grounds for Flume.
It is not so nice to use if your data needs external enrichment (taking data from external databases or web services), as transactions and (micro)batches may lead to reprocessing and it relies upon the application to avoid duplicates.

Incentivized

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.

Incentivized

• Multiple sources of data (sources) and destinations (sinks) that allows you to move data form and to any relevant data storage
• It is very easy to setup and run
• Very open to personalization, you can create filters, enrichment, new sources and destinations

Incentivized

• 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.

Incentivized

• It is very specific for log data ingestion so it is pretty hard to use for anything else besides log data
• Data replication is not built in and needs to be added on top of Apache Flume (not a hard job to do though)

Incentivized

• Had issues while using Azure ARM Templates for deployments.
• The cost structure suited for high end temporary data analytics, rather than a traditional frequently queried data warehouse.

Incentivized

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.

Incentivized

Apache Flume is open-source so support is limited. Never the less, it has great documentation and best practices documents from their end-users so it is not hard to use, setup and configure.

Incentivized

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!

Incentivized

Apache Flume is on par with Scribe with similar functions. Apache Kafka is a generation purpose while Apache Flume is specific to log aggregation. Google Pub/Sub and IBM MQ are costlier than Apache Flume ( open source ) and have a lot more cost associated with them. Apama Streaming Analytics and Tibco Steaming are more comprehensive streaming solutions than Apache Flume so for deeper performance guarantees, it is easier to use Apache Flume.

Incentivized

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.

Incentivized

• Positive impact on ROI due to a reduction in manual labor to generate and maintain compliance reports based on logs.
• Positive impact on the business objective by reducing the need for provisioning compute for log aggregate IT stack in advance but adding on an as-needed basis.

Incentivized

• ROI is of course there, as no legacy software for data presentation.
• No manual intervention for data retrieval.
• Data is available anywhere as requested.

Incentivized