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65 Ratings
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Score 8.1 out of 101
65 Ratings
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Score 8.1 out of 101

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Likelihood to Recommend

Apache Flume

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.
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Apache Hive

Apache Hive shines for ad-hoc analysis and plugging into BI tools. Its SQL-like syntax allows for ease of use not for only for engineers but also for data analysts. Through our experience, there are probably more desirable tools to use if you are planning on integrating Hive into your processing pipeline.
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Pros

  • 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
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  • SQL like query engine, allows easy ramp up from a standard RDBMS
  • Scalability is great
  • If properly configured the data retreival is fantastic
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Cons

  • Apache Flume develops new functionality at a slower pace than other OpenSource projects, it is well behing Kafka and has some compatibiliy issues with latest releases
  • It lack HA or FT, it relies on third party management software like Hortonworks or Cloudera
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  • Needs to keep up with execution engine improvements. Spark or Tez on Hive, then LLAP are good starts.
  • Overall speed of ad-hoc querying could be improved.
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Likelihood to Renew

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Apache Hive10.0
Based on 1 answer
Since I do not know the second data warehouse solution that integrate with HDFS as well as Hive.
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Usability

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Apache Hive9.0
Based on 1 answer
Hive's support SQL like queries improves its usability since almost every potential user of Hive would have had experience with SQL.
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Alternatives Considered

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.
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Hive was one of the first SQL on Hadoop technologies, and it comes bundled with the main Hadoop distributions of HDP and CDH. Since its release, it has gained good improvements, but selecting the right SQL on Hadoop technology requires a good understanding of the strengths and weaknesses of the alternative options
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Return on Investment

  • 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
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  • Allows analysts to use their SQL skills against large datasets.
  • Slow queries allow for opportunities to discover bottlenecks, parameters to tune, and alternative tools or ways to architect a system.
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Pricing Details

Apache Flume

General
Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No
Additional Pricing Details

Apache Hive

General
Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No
Additional Pricing Details