Hadoop HDFS Reviews & Product Details

The Hadoop Distributed File System (HDFS) is a scalable and fault-tolerant file system designed to manage large datasets across clusters of commodity hardware. As a core component of the Apache Hadoop ecosystem, HDFS enables efficient storage and retrieval of vast amounts of data, making it ideal for big data applications. Key Features and Functionality: - Fault Tolerance: HDFS replicates data blocks across multiple nodes, ensuring data availability and resilience against hardware failures. - High Throughput: Optimized for streaming data access, HDFS provides high aggregate data bandwidth, facilitating rapid data processing. - Scalability: Capable of scaling horizontally by adding more nodes, HDFS can accommodate petabytes of data, supporting the growth of data-intensive applications. - Data Locality: By processing data on the nodes where it is stored, HDFS minimizes network congestion and enhances processing speed. - Portability: Designed to be compatible across various hardware and operating systems, HDFS offers flexibility in deployment environments. Primary Value and Problem Solved: HDFS addresses the challenges of storing and processing massive datasets by providing a reliable, scalable, and cost-effective solution. Its architecture ensures data integrity and availability, even in the face of hardware failures, while its design allows for efficient data processing by leveraging data locality. This makes HDFS particularly valuable for organizations dealing with big data, enabling them to derive insights and value from their data assets effectively.

Seller

The Apache Software Foundation

Discussions

Hadoop HDFS Community

Solution Type

Best-of-Breed

Value at a Glance

Averages based on real user reviews.

Time to Implement

3 months

Return on Investment

19 months

View More Pricing Information

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User Insights

Average based on 141 real user reviews.

Implementation Time

3 months

Perceived Cost

$$$$$

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Verified User in Computer Software

Enterprise (> 1000 emp.)

9/3/2022

"Hadoop-Best Distributed System"

4.5/5

What do you like best about Hadoop HDFS?

Unlike another file systems, the extent to which Hadoop HDFS provides fault-tolerant is one of the best features of Hadoop. Fault-tolerant is essential for applications with high requirements. Review collected by and hosted on G2.com.

What do you dislike about Hadoop HDFS?

The major drawback I have noticed while using Hadoop is that it performs poorly when used with applications that generate small amounts of data compared to applications with large amounts of data in PB. Review collected by and hosted on G2.com.

Arpan s.

System Engineer

Enterprise (> 1000 emp.)

1/7/2022

"How hadoop is so powerful to use for data Analysis"

4.5/5

What do you like best about Hadoop HDFS?

The best part of hadoop cluster is the files storing part developer use can UI as well as the hive query language for storing the data files into the Hdfs cluster with simple commands.The file management is the best part of Hdfs cluster. Review collected by and hosted on G2.com.

What do you dislike about Hadoop HDFS?

For windows user using hdfs is little haptic because for storing a file inside a hadoop cluster they have use a 3rd party app for this called WINSCP for transfer the file from local system to unix os then after we can put it inside the Hdfs cluster. Review collected by and hosted on G2.com.

Verified User in Information Technology and Services

Enterprise (> 1000 emp.)

7/26/2022

"Hadoop HDFS Review"

4/5

What do you like best about Hadoop HDFS?

Block storage across different machines in different racks providing high availability of data and data locality for data processing minimizing the latency for data processing Review collected by and hosted on G2.com.

What do you dislike about Hadoop HDFS?

No concept of data replication across multiple availability zones like provided by public cloud and fixed cost even if minimum volume is consumed on HDFS. Review collected by and hosted on G2.com.

Kubendra Reddy M.

Data Engineer

Enterprise (> 1000 emp.)

3/4/2022

"Best distributed file system for Big Data storage and analysis"

5/5

What do you like best about Hadoop HDFS?

Best thing is it follows standard distribution architecture to store and process the data. It is highly scalable, supports different resource managers, supports different processing engines too. It can process the high volume of the parallely by using enough resources form the cluster. Review collected by and hosted on G2.com.

What do you dislike about Hadoop HDFS?

I feel little complex while learning and need to learn many commands. Maintainance is high and will take time to set up the framework. Review collected by and hosted on G2.com.

Verified User in Information Technology and Services

Enterprise (> 1000 emp.)

9/8/2022

"Recommend Hadoop"

4/5

What do you like best about Hadoop HDFS?

I like how it is very easily scalable where very high computational power can be achieved through this Review collected by and hosted on G2.com.

What do you dislike about Hadoop HDFS?

Hadoop only supports batch processing and also because of distributed algo latency increases Review collected by and hosted on G2.com.

Verified User in Automotive

Enterprise (> 1000 emp.)

8/24/2022

"HDFS review"

4.5/5

What do you like best about Hadoop HDFS?

Distributed storage and high availability of data. Multiple processing engines supported like MR Tez and spark Review collected by and hosted on G2.com.

What do you dislike about Hadoop HDFS?

Slow adhoc queries for analytics. No concept of faster reads like AWS Athena. Review collected by and hosted on G2.com.

Chintan M.

Assistant System Engineer

Mid-Market (51-1000 emp.)

9/28/2021

"How Hadoop HDFS is best file system for Big Data applications."

5/5

What do you like best about Hadoop HDFS?

I am using Hadoop HDFS for the last 3 months in my Big Data training. I used Hadoop HDFS with different Hadoop tools like MapReduce, Hive, Pig, and Spark. I like the features of replication in Hadoop HDFS where we can store data with the 3 same copies so we can achieve fault tolerance. When we store data into Hadoop HDFS that time our data will be split into small chunks and then it will store into different nodes so I/O will be done parallelly. Even we can change replication in Hadoop HDFS. If we store files and data into Hadoop HDFS so we can use that data in different Hadoop tools like Hive, Pig, Spark, and MapReduce. I also store MySQL database's table data into Hadoop HDFS into CSV format. I also export data from Hadoop HDFS to the MySQL database's table. If you are working with Big Data then Hadoop HDFS is a very important tool for you so I strongly recommend you to use Hadoop HDFS to store the data and use that data in different tools. Review collected by and hosted on G2.com.

What do you dislike about Hadoop HDFS?

Hadoop HDFS is the best distributed file system in the Hadoop ecosystem. If we create a replica then it will consume more storage as compare to a single copy so you have to make sure that If you don't need fault tolerance then avoid replicas. Review collected by and hosted on G2.com.

Recommendations to others considering Hadoop HDFS:

I strongly recommend using Hadoop HDFS as a storage system in Big Data applications. Review collected by and hosted on G2.com.

What problems is Hadoop HDFS solving and how is that benefiting you?

Usually, I have lots of data in the MySQL database. I have to process that data and retrieve information from that data and again store that information in MySQL. When I tried without Hadoop HDFS so there is not any tool available in the market to do this work in an easy and simple way. I tried with the Hadoop HDFS then It became very easy and simple. I import data from MySQL to Hadoop HDFS using Sqoop. I processed that data and store it in Hadoop HDFS. I exported processed data from Hadoop HDFS to MySQL table using Sqoop again and yah my job is done. Sometimes our projects needed fault tolerance then the replication feature of Hadoop HDFS is very useful to our team. Hadoop HDFS splits the data into small chunks so we can do read, write operations simultaneously. Review collected by and hosted on G2.com.

Lee T.

Market Strategy Planning Manager

Enterprise (> 1000 emp.)

9/17/2021

"Efficient tool for large amount of data processing"

4.5/5

What do you like best about Hadoop HDFS?

Hadoop HDFS is one of the data processing software that has supported and distributed all processing plus data storage as well. This product is mainly known for its reliability, functionality, and scalability all across the hardware industry. The most important reason for us using this software is because we wanted to solve the problem related to attaining insights into such large business data. It is quite powerful and has a strong programming model that can be used from either Java Programming language or even other languages that are flown by the data flow. This product also has a great framework for building all of the different processing teams which are developed for lower levels of latency and a high-performance level. It also has an ecosystem that is rural just in order to create complex data. Review collected by and hosted on G2.com.

What do you dislike about Hadoop HDFS?

I think that the development tools which are in the software are a little difficult and sometimes I feel these points to be a little difficult to use. Also, the learning curve should be mitigated to a considerable extent as there are certain skills that a person does not have. Review collected by and hosted on G2.com.

Recommendations to others considering Hadoop HDFS:

The development tools which are in the software are a little difficult and sometimes I feel these points to be a little difficult to use. Also, the learning curve should be mitigated to a considerable extent as there are certain skills that a person does not have. After evaluating both the positive and negative of this famous software I came to the conclusion that this software is a great software and it will generate even better and more refined results in a large company because I think that this software is more suited for unstructured software. Review collected by and hosted on G2.com.

What problems is Hadoop HDFS solving and how is that benefiting you?

It is quite easy to use and also easy to set up the initial processing. Moreover, there is a lot of fault tolerance within the platform that makes it a great choice. Also, there is a low learning curve within the platform which enhances the usability of the platform. Altogether, this product has made everything quite easy. With all my experience I think that this product is a very reliable and a good solution which has the audacity to process large data sets in different servers. This software can automatically gauge the number of machines that are required for processing and analyzing. Hence, I think that this software is undoubtedly the best software in this category. Review collected by and hosted on G2.com.

Pawan K.

Bigdata Platform Architect at HCL Technologies Limited

Enterprise (> 1000 emp.)

1/20/2022

"Offline batch process for high volume and multi format of data"

4/5

What do you like best about Hadoop HDFS?

Distributed file system process and multi-tenant environments Review collected by and hosted on G2.com.

What do you dislike about Hadoop HDFS?

More admin works required for cluster management Review collected by and hosted on G2.com.

Ankit K.

System QA Sr Analyst

Enterprise (> 1000 emp.)

12/14/2021

"Most reliable filesystem"

4.5/5

What do you like best about Hadoop HDFS?

Unique design that provides storage for extremely large files with streaming data access pattern and run on commodity hardware. Review collected by and hosted on G2.com.

What do you dislike about Hadoop HDFS?

Security concern, managing a complex application can be challenging. Vulnerable by nature, not fit for small data. Review collected by and hosted on G2.com.