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Apache Hadoop pros and cons

Vendor: Apache

3.9 out of 5

39 reviews
89% willing to recommend

1,782 followers

Pros & Cons summary

Apache Hadoop offers scalability and parallel processing for large data volumes, integrating with tools like HDFS and Kafka for data ingestion. It supports AI and machine learning with cost-effective processing and flexible storage across data formats. Its open-source nature aids infrastructure integration, though it faces issues with memory-intensive queries and lacks comprehensive virtualization. Data migration and security need enhancements, and its complex ecosystem may require external consultation for feature selection.

Buyer's Guide

Get pricing advice, tips, use cases and valuable features from real users of this product.

Prominent pros & cons

PROS

Apache Hadoop's scalability and parallel processing capabilities allow it to handle large volumes of data with ease.

Its integration capacity supports various tools in a big data platform, enhancing its utility and flexibility.

The system offers cost-effectiveness as an open-source platform, making it ideal for big data projects.

Data ingestion and processing speed aid in supporting AI-driven and analytics projects efficiently.

Apache Hadoop's ability to store and manage structured, unstructured, and semi-structured data makes it versatile for extensive data handling.

CONS

Apache Hadoop's inability to handle queries efficiently with insufficient memory remains a key shortcoming.

Migration from MySQL to Hive presents challenges, necessitating support from forums and trial and error.

Direct integration of visualization applications and advanced analytics tools is desired.

Real-time data processing capabilities are weak and need improvement.

The system lacks adequate community support and comprehensive training materials for new users.

Apache Hadoop Pros review quotes

reviewer1384338

Vice President - Finance & IT at a consumer goods company with 1-10 employees

Jul 14, 2020

The solution is easy to expand. We haven't seen any issues with it in that sense. We've added 10 servers, and we've added two nodes. We've been expanding since we started using it since we started out so small. Companies that need to scale shouldn't have a problem doing so.

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Co-Founder at Quantic

Jul 18, 2022

The most important feature is its ability to handle large volumes. Some of our customers have really large volumes, and it is capable of handling their data in terms of the core volume and daily incremental volume. So, its processing power and speed are most valuable.

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reviewer1976262

Credit & Fraud Risk Analyst at a financial services firm with 10,001+ employees

Sep 29, 2022

Apache Hadoop can manage large amounts and volumes of data with relative ease, which is a feature that is beneficial.

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Juliet Hoimonthi

Manager at Robi Axiata Limited

Jul 5, 2022

What I like about Apache Hadoop is that it's for big data, in particular big data analysis, and it's the easier solution. I like the data processing feature for AI/ML use cases the most because some solutions allow me to collect data from relational databases, while Hadoop provides me with more options for newer technologies.

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AM

CEO

Mar 6, 2018

Initially, with RDBMS alone, we had a lot of work and few servers running on-premise and on cloud for the PoC and incubation. With the use of Hadoop and ecosystem components and tools, and managing it in Amazon EC2, we have created a Big Data "lab" which helps us to centralize all our work and solutions into a single repository. This has cut down the time in terms of maintenance, development and, especially, data processing challenges.

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Software developer at Fiserv

Jun 25, 2024

It is a reliable product.

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reviewer1040328

IT Expert at a tech services company with 1,001-5,000 employees

Jul 28, 2019

The best thing about this solution is that it is very powerful and very cheap.

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Samuel Feinberg

Analytics Platform Manager at a consultancy with 10,001+ employees

Aug 14, 2018

Two valuable features are its scalability and parallel processing. There are jobs that cannot be done unless you have massively parallel processing.

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reviewer2324613

Data Architect at a computer software company with 51-200 employees

Dec 29, 2023

It's open-source, so it's very cost-effective.

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Data Engineer at BBD

Sep 29, 2019

What comes with the standard setup is what we mostly use, but Ambari is the most important.

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Apache Hadoop Cons review quotes

reviewer1384338

Vice President - Finance & IT at a consumer goods company with 1-10 employees

Jul 14, 2020

The solution needs a better tutorial. There are only documents available currently. There's a lot of YouTube videos available. However, in terms of learning, we didn't have great success trying to learn that way. There needs to be better self-paced learning.

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Co-Founder at Quantic

Jul 18, 2022

It requires a great deal of learning curve to understand. The overall Hadoop ecosystem has a large number of sub-products. There is ZooKeeper, and there are a whole lot of other things that are connected. In many cases, their functionalities are overlapping, and for a newcomer or our clients, it is very difficult to decide which of them to buy and which of them they don't really need. They require a consulting organization for it, which is good for organizations such as ours because that's what we do, but it is not easy for the end customers to gain so much knowledge and optimally use it.

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reviewer1976262

Credit & Fraud Risk Analyst at a financial services firm with 10,001+ employees

Sep 29, 2022

I mentioned it definitely, and this is probably the only feature we can improve a little bit because the terminal and coding screen on Hadoop is a little outdated, and it looks like the old C++ bio screen. If the UI and UX can be improved slightly, I believe it will go a long way toward increasing adoption and effectiveness.

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Juliet Hoimonthi

Manager at Robi Axiata Limited

Jul 5, 2022

What could be improved in Apache Hadoop is its user-friendliness. It's not that user-friendly, but maybe it's because I'm new to it. Sometimes it feels so tough to use, but it could be because of two aspects: one is my incompetency, for example, I don't know about all the features of Apache Hadoop, or maybe it's because of the limitations of the platform. For example, my team is maintaining the business glossary in Apache Atlas, but if you want to change any settings at the GUI level, an advanced level of coding or programming needs to be done in the back end, so it's not user-friendly.

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AM

CEO

Mar 6, 2018

Based on our needs, we would like to see a tool for data visualization and enhanced Ambari for management, plus a pre-built IoT hub/model. These would reduce our efforts and the time needed to prove to a customer that this will help them.

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Software developer at Fiserv

Jun 25, 2024

There are certain shortcomings when it comes to the product's technical support part, making it an area where improvements are required.

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reviewer1040328

IT Expert at a tech services company with 1,001-5,000 employees

Jul 28, 2019

The upgrade path should be improved because it is not as easy as it should be.

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SF

Samuel Feinberg

Analytics Platform Manager at a consultancy with 10,001+ employees

Aug 14, 2018

I would like to see more direct integration of visualization applications.

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reviewer2324613

Data Architect at a computer software company with 51-200 employees

Dec 29, 2023

The main thing is the lack of community support. If you want to implement a new API or create a new file system, you won't find easy support.

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Data Engineer at BBD

Sep 29, 2019

In the next release, I would like to see Hive more responsive for smaller queries and to reduce the latency.

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Show 10 more reviews (out of 33)

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