Hadoop

Hadoop

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Score 8.5 out of 100
Apache Hadoop

Overview

Recent Reviews

Hadoop vs. Alternatives

8 out of 10
June 05, 2019
It is being used at our Fortune 500 clients. It is great for storage, but it is not well understood by the business. The challenge is that …
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Hadoop Review

7 out of 10
May 16, 2018
It is massively being used in our organization for data storage, data backup, and machine learning analytics. Managing vast amounts of …
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Hadoop is pretty Badass

9 out of 10
January 04, 2018
Apache Hadoop is a cost effective solution for storing and managing vast amounts of data efficiently. It is dependable and works even when …
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Hadoop review 2346

9 out of 10
September 22, 2017
Hadoop is used to build a data lake where all enterprise data for my entire company can be stored. With data centralization and …
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What is Hadoop?

Hadoop is an open source software from Apache, supporting distributed processing and data storage. Hadoop is popular for its scalability, reliability, and functionality available across commoditized hardware.

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Features Scorecard

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Product Details

What is Hadoop?

Hadoop is an open source software from Apache, supporting distributed processing and data storage. Hadoop is popular for its scalability, reliability, and functionality available across commoditized hardware.

Hadoop Video

What is Hadoop?

Hadoop Integrations

  • Sematext Infrastructure Monitoring (formerly Sematext SPM)

Hadoop Technical Details

Operating SystemsUnspecified
Mobile ApplicationNo

Comparisons

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Frequently Asked Questions

What is Hadoop?

Hadoop is an open source software from Apache, supporting distributed processing and data storage. Hadoop is popular for its scalability, reliability, and functionality available across commoditized hardware.

What is Hadoop's best feature?

Reviewers rate Data Sources highest, with a score of 8.7.

Who uses Hadoop?

The most common users of Hadoop are from Enterprises (1,001+ employees) and the Information Technology & Services industry.

Reviews

(1-25 of 37)
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Kunal Sonalkar | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
Hadoop is being used to solve big data modeling problems in our firm. The corporate analytics team uses Hadoop to perform functions like data manipulation, information retrieval, data mapping, and statistical modeling. The business problem which it solves is the limitation of CSV/Excel files to handle more than a million rows. Hadoop allows you to process big data and also has connectivity with platforms like R Studio where you can deploy mathematical models.
Chantel Moreno | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
Apache Hadoop is one of the most effective and efficient software which has been storing and processing an extremely colossal amount of data in my company for a long time now. The software Hadoop is primarily used for data collection of large amounts, storage as well as for analytics. From my experience, I have to say that Hadoop is extremely useful and has a reliable plus valid purpose.
Peter Suter | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
Apache Hadoop is an open-source software library that is designed for the collection, storage, and analysis of large amounts of data sets. Apache Hadoop’s architecture comprises components that include a distributed file system. This is mostly used for massive data collection, analytics, and storage. Also, having consistent data can be integrated across other platforms and have one single source of truth.
Score 7 out of 10
Vetted Review
Verified User
Review Source
We use Apache Hadoop to store and process large amounts of data (petabytes per day) across thousands of data pipelines. Hadoop works reliably for this purpose. Data scientists at the company also use it for interactive querying for analytics and modeling purposes.
Score 7 out of 10
Vetted Review
Verified User
Review Source
[Apache Hadoop] is being handled as it is (mostly) intended. For large, unstructured data management from our data flows to include logging and reports extract, transform and load. We are using it at a medium scale in an on-prem server delivery with Cloudera as the management platform. While I firmly believe cloudera makes it a bit easier to manage, it obfuscates issues at times.
Blake Baron | TrustRadius Reviewer
Score 7 out of 10
Vetted Review
Verified User
Review Source
It's used organization-wide for older data that's not used as frequently. We use Teradata to warehouse our more recent data, but for data we don't access as often, it's migrated to Hadoop. It addresses the problem of securely storing data without paying the fortune that most warehouses charge for premium cloud storage.
Gene Baker | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
We are using it within my department to process large sets of data that can't be processed in a timely fashion on a single computer or node. The various modules provided with Hadoop make it easy for us to implement map-reduce and perform parallel processing on large sets of data. We have approximately 40TB of data that we run various algorithms against as we try to use the data to solve business problems and prevent fraudulent transactions.
Mark McCully | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
We leverage Hadoop for several of our Tier 1 applications. We use Hadoop for our enterprise data lake where all of the data that our company takes in from our members is stored and then a lot of our applications use that as their master datasource. We also leverage Hadoop clusters for Paxata and Data Scientist analytics workloads. Basically, anything that requires a scale-out approach, we put on Hadoop.
Score 8 out of 10
Vetted Review
Verified User
Review Source
It is being used at our Fortune 500 clients. It is great for storage, but it is not well understood by the business. The challenge is that it requires very sophisticated data scientists to use properly and in parallel, but the data scientists turn the data on its head, causing IT execution issues. This has forced IT to restructure data in a denormalized form so the business users can actually be productive. This is a big trend in organizations.
May 16, 2018

Hadoop Review

Kartik Chavan | TrustRadius Reviewer
Score 7 out of 10
Vetted Review
Verified User
Review Source
It is massively being used in our organization for data storage, data backup, and machine learning analytics. Managing vast amounts of data has become quite easy since the arrival of the Hadoop environment. Our department is on verge of moving towards Spark instead of MapReduce, but for now, Hadoop is being used extensively for MapReduce purposes.
Bharadwaj (Brad) Chivukula | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
  • Used for Massive data collection, storage, and analytics
  • Used for MapReduce processes, Hive tables, Spark job input, and for backing up data
  • Storing Retail Catalog & Session data to enable omnichannel experience for customers, and a 360-degree customer insight
  • Having a consistent data store that can be integrated across other platforms, and have one single source of truth.
January 04, 2018

Hadoop is pretty Badass

Score 9 out of 10
Vetted Review
Verified User
Review Source
Apache Hadoop is a cost effective solution for storing and managing vast amounts of data efficiently. It is dependable and works even when various clusters fail. The Hadoop Distributed File System (HDFS) also goes a long way in helping in storing data. MapReduce and Tez, with the help of Hive of course, processes large amounts of data in a lesser time frame than expected. This helps our data warehouse to be updated with lesser resources rather than reading, processing and updating data in a relational data base.
Johanes Siregar | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Review Source
Currently, there are two directorates using Hadoop for processing a vast amount of data from various data sources in my organization. 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.
Score 10 out of 10
Vetted Review
Verified User
Review Source
Hadoop has been an amazing development in the world of Big Data. 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 datapoints.
September 22, 2017

Hadoop review 2346

Gyan Dwibedy | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
Hadoop is used to build a data lake where all enterprise data for my entire company can be stored. With data centralization and standardization we use it to build analytical solutions for our company. There are many other uses for the data - for example monitoring performance via KPIs, etc.
Mark Gargiulo | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Review Source
We needed a robust/redundant system to run multiple simultaneous jobs for our ETL pipeline, this needed distributed storage space, integration with Windows AD user accounts and the ability to expand when needed with little to no downtime.
We are using Cloudera 5.6 to orchestrate the install (along with puppet) and manage the hadoop cluster.
Muhammad Fazalul Rahman | TrustRadius Reviewer
Score 7 out of 10
Vetted Review
Verified User
Review Source
Hadoop is not used as a norm in my organization. I just use it personally to complete my job faster. It is implemented in the research computing cluster to be used by faculty and students. It completes jobs faster by parallelizing the tasks using MapReduce framework. This gives me considerable speed in the tasks I perform.
Tom Thomas | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
The company I worked at used Hadoop clusters for processing huge datasets. They had several nodes for both production and per-production nodes. It allowed distributed processing of data across several clusters with an easy to use software model. It is used by the Systems and IT department at my company.
February 23, 2016

Hadoop quick review

Score 9 out of 10
Vetted Review
Verified User
Review Source
We have Hadoop pre-prod and prod clusters. Production clusters are comprised of 200 nodes. And we have realtime clusters as well. All the data will be moved to Hadoop. We use Hadoop to do machine learning and data warehousing.
Piyush Routray | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
My present company uses Hadoop and associated technology to create a data pipeline using open source tools. Apart from that we also consult for projects which could potentially use Hadoop. Apart from that, I also work as a consultant for HDP. We actively help in installation and setup of hadoop clusters.
Tushar Kulkarni | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
I have been working with Hadoop since last year. It is very user friendly. Hadoop was used by the data center management team. It allows distributed processing of huge amount of data sets across clusters of computers using simple programming models.
Score 9 out of 10
Vetted Review
Verified User
Review Source
My organization uses Apache Hadoop for log analysis/data mining of data fetched from different practices in the US, Canada and India. It uses this data for showing analytical graphs and the progress of our software in those regions. Data from the practices is optimized and consumed by the customer applications. It provides faster performance and ease for data usage.
Pierre LaFromboise | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
We utilize Hadoop primarily as a large data staging area for disparate corporate data. Select data is aggregated and moved downstream to a more formal data warehouse. Some data analytics is also performed directly against the Hadoop stored data. The direct analytics is done primarily with Apache Spark utilizing Scala and Python.
Mrugen Deshmukh | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Review Source
I have used Hadoop for building business feeds for a telecom client. The major purpose for using Hadoop was to tackle the problem of gaining insights into the ever growing number of business data. We leveraged the map reduce programming model to churn more than 30 gigabytes of data per day into actionable and aggregated data which was further leveraged by campaign teams to design and shape marketing and by product teams to envision new customer experiences.