What users are saying about

Apache Flume

5 Ratings

Hadoop

211 Ratings

Apache Flume

5 Ratings
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Score 7.9 out of 101

Hadoop

211 Ratings
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Score 8 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.
Juan Francisco Tavira profile photo

Hadoop

Hadoop helps us tackle our problem of maintaining and processing a huge amount of data efficiently. High availability, scalability and cost efficiency are the main considerations for implementing Hadoop as one of the core solutions in our big-data infrastructure. Where relational databases fall short with regard to tuning and performance, Hadoop rises to the occasion and allows for massive customization leveraging the different tools and modules. We use Hadoop to input raw data and add layers of consolidation or analysis to make business decisions about disparate data points.
Kartik Chavan profile photo

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
Juan Francisco Tavira profile photo
  • Hadoop Distributed Systems is reliable.
  • High scalability
  • Open Sources, Low Cost, Large Communities
Kartik Chavan profile photo

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
Juan Francisco Tavira profile photo
  • Hadoop is not a relational database, but it has the ability to add modules to run sql-like queries like Impala and Hive.
  • Hadoop is open source and has many modules. It can be difficult without context to know which modules to leverage.
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Likelihood to Renew

No score
No answers yet
No answers on this topic
Hadoop9.6
Based on 8 answers
Hadoop is still young and evolving. There is a lot of potential and undiscovered uses for it.
Michael Reynolds profile photo

Usability

No score
No answers yet
No answers on this topic
Hadoop9.0
Based on 3 answers
I found it really useful during my academic projects. Data handling for large data sets was easy with Hadoop. It used to work really fast for bigger data sets. I found it reliable.
Tushar Kulkarni profile photo

Online Training

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Hadoop6.1
Based on 2 answers
Hadoop is a complex topic and best suited for classrom training. Online training are a waste of time and money.
Bhushan Lakhe profile photo

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.
Juan Francisco Tavira profile photo
I haven't worked with other Big Data aggregation services like Hadoop. As far as I know, Hadoop is the leading choice in this field with good cause. There is a lot of community support, custom modules, paid consultants, free and paid training. All this makes it an ideal choice for facilitating Big Data aggregation.
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Collaboration and Sharing

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Hadoop7.7
Based on 10 answers
  • Access control measures: Apache Sentry provides fine grained role based authorization to data and metadata stored on a Hadoop clusters.Distributed scheduling and coordination of jobs via use of YARN and Apache Oozie.Availability of improved reporting and dashboards for Hadoop via use of vendor driven distributions like
  • Distributed scheduling and coordination of jobs via use of YARN and Apache Oozie.
  • Availability of improved reporting and dashboards for Hadoop via use of vendor driven distributions like Cloudier CDH.
Mrugen Deshmukh profile photo

Data Integration

No score
No answers yet
No answers on this topic
Hadoop8.7
Based on 10 answers
We have used sensors data as a source. Hadoop handles streaming data seamlessly and processes it on the fly
Tushar Kulkarni profile photo

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
Juan Francisco Tavira profile photo
  • Hadoop has an amazing potential for ROI if implemented properly to justify business decisions.
  • Hadoop can allow groups to understand how their work is impacting performance at a high level, such as page clicks, where people are spending their time, how users are engaging with the application, etc.
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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

Hadoop

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