Apache Flume vs. Hydrograph

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

hydrograph is very usefull when we need to analyze big data. in our scenario it helped a lot with rdms databases

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

• Coupling between complex model and MapReduce framework without reducer procedure was simplified.
• The ability to reduce execution time and handle partial failure
• The framework adapts to higherned complex model

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

• Microsoft azure is recently joined in 2020 that can be improved.

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

Snap logic fits good for small/medium whereas hydrograph suits even for Enterprise grade.

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

• Their is no tangible ROI for us Management of bid data is easy.

Incentivized