Apache Flume vs. Kognitio

Apache Flume is well suited when the use case is log data ingestion and aggregate only, for example for compliance of configuration management. It is not well suited where you need a general-purpose real-time data ingestion pipeline that can receive log data and other forms of data streams (eg IoT, messages).

Incentivized

What you have are different strategies for data encoding, which makes the process quite flexible, it is perfectly done so that a joint and collaborative work can be carried out, this information analyzed in large quantities, is extremely vital for the company, by giving it the correct and timely reading

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

• Ultra fast query results.
• IN Memory Database.
• Easy integration to reporting services.

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

• Problems Could Be Encountered is particularly pronounced in more complex analyses.
• Categorical variables are often not precise enough

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

Apache Flume is a very good solution when your project is not very complex at transformation and enrichment, and good if you have an external management suite like Cloudera, Hortonworks, etc. But it is not a real EAI or ETL like AB Initio or Attunity so
you need to know exactly what you want. On the other hand being an opensource project give Apache a lot of room to personalize thanks to its plug-able architecture and has a very nice performance having a very low CPU and Memory footprint, a single server can do the job on many occasions, as opposed to the multi-server architecture of paid products.

Incentivized

We selected Kognitio because of the legacy systems that are still running. Also, we have legacy systems in place that are fit for Kognitio. End-user has good feedback on our side when we started implementing this solution. Current servers are compatible with Kognitio in place.

Incentivized

• Flume has simplified a lot many of our ingest procedures, easier to deploy and integrate than a classical EAI, reducing the time to market
• But opposed to EAIs if the project starts to grow in complexity Apache Flume project may not be as suitable

Incentivized

• The implementation of the formats to integrate the users we have and the program is also good.
• I also improve the control of aspects related to the work environment

Incentivized