--- title: Hadoop HDFS Reviews meta_title: 'Hadoop HDFS Reviews 2026: Details, Pricing, & Features | G2' meta_description: Filter 141 reviews by the users' company size, role or industry to find out how Hadoop HDFS works for a business like yours. aggregate_rating: rating_value: 4.4 review_count: 141 scale: '5' date_modified: '2026-07-17' parent_category: name: Big Data url: https://www.g2.com/categories/big-data --- # Hadoop HDFS Reviews **Vendor:** The Apache Software Foundation **Category:** [Big Data Processing And Distribution Systems](https://www.g2.com/categories/big-data-processing-and-distribution) **Average Rating:** 4.4/5.0 **Total Reviews:** 141 ## About Hadoop HDFS 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. ## Hadoop HDFS Pros & Cons **What users like:** - Users commend HDFS for its **excellent data processing** capabilities, ensuring reliable storage and robust fault tolerance. (1 reviews) - Users value the **data security** of Hadoop HDFS, appreciating its fault tolerance for large file storage across machines. (1 reviews) - Users value the **reliable data storage** of Hadoop HDFS, appreciating its fault tolerance and stability in big data processing. (1 reviews) - Users value the **storage of large files across multiple machines** with solid fault tolerance and stability of HDFS. (1 reviews) **What users dislike:** - Users find the **increased costs** associated with HDFS due to hardware and maintenance burdens quite challenging. (1 reviews) - Users face significant **maintenance issues** with HDFS, requiring dedicated teams for security, upgrades, and overall management. (1 reviews) - Users face significant **performance issues** with HDFS, struggling with scaling, management, and inefficiency in handling small files. (1 reviews) - Users highlight **poor performance** issues with HDFS, struggling with scaling and management challenges in modern environments. (1 reviews) - Users highlight **security issues** with Hadoop HDFS, requiring a dedicated team for upgrades and maintenance. (1 reviews) ## Hadoop HDFS Reviews ### 1. Good storage **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Information Services | Enterprise (> 1000 emp.) **Reviewed Date:** August 23, 2019 **What do you like best about Hadoop HDFS?** I like the ease of use of the hardtop hdfs(Hadoop File System). It is very simple and easy to use. It is used mainly to store all our hadoop applications that we create. **What do you dislike about Hadoop HDFS?** It needs the knowledge of different technologies which I did not think was necessary. I do not use this very often since we do not Hadoop that often. **Recommendations to others considering Hadoop HDFS:** It is a nice and easy data storage system for all your hadoop application needs. Do not use for other applications other than hadoop applications **What problems is Hadoop HDFS solving and how is that benefiting you?** We are using it as a data storage system to store the Hadoop applications we created. The main benefits we have realized is that it is a simple and low cost data storage system for storing all of our Hadoop applications that we have created. ### 2. Hadoop review **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Education Management | Mid-Market (51-1000 emp.) **Reviewed Date:** October 28, 2019 **What do you like best about Hadoop HDFS?** Hadoop is a great tool for data scientists, and if you are working on large databases and great amount of data, it helps you to sort and define data and their use. **What do you dislike about Hadoop HDFS?** If you do not know the structure and the architecture of the Hadoop, it is hard to know what are you looking for and how to get the benefits. **Recommendations to others considering Hadoop HDFS:** Please enable resizing large data files. **What problems is Hadoop HDFS solving and how is that benefiting you?** Sorting large files and databases, if you are looking for a power tool for large sets of data. It can sort it all. ### 3. secure and reliable **Rating:** 5.0/5.0 stars **Reviewed by:** Kritika G. | Software Engineer, Computer Software, Small-Business (50 or fewer emp.) **Reviewed Date:** April 03, 2019 **What do you like best about Hadoop HDFS?** it is one of the best-distributed file systems. It secure, handle large file system, reliable. Easy to access all data. nice integration with HiveQL, pig, sqoop, and flume. its capability to replicate data across the different cluster is very secure. **What do you dislike about Hadoop HDFS?** the accuracy with small data sets is zero. min file size should be greater than hdfs block size. even for testing purpose, you need a bigger data set. **Recommendations to others considering Hadoop HDFS:** If you are working with large datasets and need to distribute data on diffrent nodes.and if you handling private data. **What problems is Hadoop HDFS solving and how is that benefiting you?** Storing data, moving data from one database to another. running batch jobs on saved data.Currently working on 4 node cluster. ### 4. Handling varied data resources **Rating:** 3.5/5.0 stars **Reviewed by:** Rajat S. | Business Analyst- Consulting (E-commerce, Risk ), Enterprise (> 1000 emp.) **Reviewed Date:** October 10, 2019 **What do you like best about Hadoop HDFS?** Good for large number of data easy execution User friendly interface scalable low traffic network less cost **What do you dislike about Hadoop HDFS?** issue with small files iterative processing security small batch processing **Recommendations to others considering Hadoop HDFS:** go for this for handling large sets of data with low traffic and low cost **What problems is Hadoop HDFS solving and how is that benefiting you?** Getting large sets of data ### 5. Hadoop **Rating:** 3.0/5.0 stars **Reviewed by:** Saurabh A. | ETL Lead, Enterprise (> 1000 emp.) **Reviewed Date:** October 03, 2019 **What do you like best about Hadoop HDFS?** High volume data processing power Data duplication across nodes Ease of data storage **What do you dislike about Hadoop HDFS?** System becomes slow since nodes are shared, so it becomes difficult to complete job execution **What problems is Hadoop HDFS solving and how is that benefiting you?** Data retention and ease of data analytics ### 6. Hadoop HDFS **Rating:** 5.0/5.0 stars **Reviewed by:** Deepti A. | IAM / Security Engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** September 21, 2018 **What do you like best about Hadoop HDFS?** The big problem that Hadoop HDFS solves is to store big data and process big data. It processes big data using Map reduce. Big data is a huge issue now and Hadoop can solve it! So, this is what I like about Hadoop HDFS. I believe it's open source, so doesn't really cost anything to install and start using it **What do you dislike about Hadoop HDFS?** Honestly, there is nothing to dislike about Hadoop. Hadoop is fairly a new technology that is benefiting a lot of companies. But, if you want to install in your PC, you require a high configuration laptop - 16GB RAM and a better processor. **Recommendations to others considering Hadoop HDFS:** As I mentioned earlier, it greatly benefits organizations to store their data and to process the data when ever they want. Hadoop is already benefiting a lot of organizations with their data. **What problems is Hadoop HDFS solving and how is that benefiting you?** As I mentioned Hadoop has been introduced to solve big data..My company and many other companies want to store data in HDFS, and when they want to process some of the data Hadoop map reduce comes into picture! ### 7. nice datawarehouse **Rating:** 4.5/5.0 stars **Reviewed by:** Kanik G. | Technical Specialist, Information Technology and Services, Enterprise (> 1000 emp.) **Reviewed Date:** April 23, 2019 **What do you like best about Hadoop HDFS?** Its a nice storage to store metadata. stores data in master slave architecture which makes it very scalable, very secure. Provide a stable integration with all the hadoop ecosystem components like hive,pig,sqoop,flume. currently integration with spark on the to top of spark standlone ecosystem makes it more useful. **What do you dislike about Hadoop HDFS?** nothing i can think of right now.i love this storage warehouse. **What problems is Hadoop HDFS solving and how is that benefiting you?** working on own 4 node cluster. has integration with hive,oozie workflow ### 8. HDFS **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Financial Services | Mid-Market (51-1000 emp.) **Reviewed Date:** February 14, 2019 **What do you like best about Hadoop HDFS?** HDFS allows for us to achieve data analytics on big data at a level that we were previously unable to realize. I find the system very easy to use, and I know that it will benefit in the future. **What do you dislike about Hadoop HDFS?** I really don't think that there is anything to dislike about the system. **What problems is Hadoop HDFS solving and how is that benefiting you?** Bid data analytics has never been easier. ### 9. Brilliant for data mining across large cache rdbms **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Banking | Enterprise (> 1000 emp.) **Reviewed Date:** February 16, 2018 **What do you like best about Hadoop HDFS?** Hadoop can take loads of data from disparate sources quickly and performs well under testing performance conditions with multi-server configurations. Hadoop is customizable so that nearly and most of our business objectives can be justified with the right combination of data and reports. Very scalable product for infinite number of rows and large number of parallel processors through dynamic clustering. THe product is also very economical in comparison to SAS. **What do you dislike about Hadoop HDFS?** Less organizational support system. Bugs that need help outside help take a long time to get pushed as an update. Does not come with too much business knowledge hence the container needs a lot of programming to make usable for a specific use case. **Recommendations to others considering Hadoop HDFS:** use if you have a heavy dataset (most other solutions will not work in this case). it is economical in the medium to long term although the implementation is higher than for most other cloud-based solutions. **What problems is Hadoop HDFS solving and how is that benefiting you?** using hdfs for storage and processing. intermediate data filtering as a middleware ### 10. Hadoop HDFS Review **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Broadcast Media | Enterprise (> 1000 emp.) **Reviewed Date:** August 06, 2018 **What do you like best about Hadoop HDFS?** Ease of accessibility via terminal using standard bash commands. **What do you dislike about Hadoop HDFS?** There are a few UIs to access it without terminal, but we could use one which is bug free and has all features. **Recommendations to others considering Hadoop HDFS:** Definitely should try this out and think about switching from current file management system to this one. While it may take some time to get used to it, once done it will be super easy to use and improve current implementations. **What problems is Hadoop HDFS solving and how is that benefiting you?** Data storage and code sharing. ### 11. Store anything and everything **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Insurance | Enterprise (> 1000 emp.) **Reviewed Date:** July 31, 2018 **What do you like best about Hadoop HDFS?** Storage capability, reliability, robustness, scalability. Can access through different tools. **What do you dislike about Hadoop HDFS?** Data stored in key and value format.sometimes the query gets stuck. **What problems is Hadoop HDFS solving and how is that benefiting you?** The amount of data that organisation have generated ,conventional database scalability was a challenge with added cost. Hadoop hdfs resolves the problem. ### 12. I face with bugs in fedora but not in ubuntu **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Small-Business (50 or fewer emp.) **Reviewed Date:** July 13, 2018 **What do you like best about Hadoop HDFS?** hadoop is one of the best softwares especially for cloud computing engineers. **What do you dislike about Hadoop HDFS?** i face with so many problems when I want change my java version. seems silly but every time i wanna go to a higher version this happens to me. **What problems is Hadoop HDFS solving and how is that benefiting you?** I am working on data analytics ### 13. Data Lake HDFS **Rating:** 4.0/5.0 stars **Reviewed by:** swetha m. | Senior System Engineer, Information Technology and Services, Enterprise (> 1000 emp.) **Reviewed Date:** September 13, 2017 **What do you like best about Hadoop HDFS?** 1) Distributed File System helps in partitioning huge data into multiple machines which helps in storing peta data,it follows write once and follows WORM-write ones read many times. 2) We have master node to distribute data among nodes and maintain the metadata of file version and path in it which is easier to spot the files. 3) Data Loss- As data is stored in multiple data nodes, there is a replication in case of any failure and very less chance to lose data. 4) Reading, copying, moving files to HDFS using putty commands is easier. 5) Apache ambari provides the user interface for Hadoop eco-systems which helps us to download,copy,rename,move and change permissions to directory and files in HDFS more easier. 6) Use of checksum for data integrity helps to check corruption of data. **What do you dislike about Hadoop HDFS?** 1) Failure in namenode has no replication which takes lot of time to recover. 2) As Block size has a limit in size,storing small files is not efficient. 3) It doesn't allow multiple users to write to a file. **Recommendations to others considering Hadoop HDFS:** 1) HDFS is a filesystem which has huge memory and can store your files in a distributed manner in multiple network machines. 2) Follows Write ones and read multiple times slogan along with replication of data in data nodes. 3) we have master node to distribute data among nodes and maintain the metadata of file version and path in it which is easier to spot the file **What problems is Hadoop HDFS solving and how is that benefiting you?** 1) We are able to load peta bytes of metadata to Hbase using map reduce programs by creating H file in HDFS 2) We are able to scheedule our jobs by keeping the relevant files in HDFS by oozie yarn user. 3) We are able to store both content(any flat file) and metadata in the form of H file in HDFS and finally load to Hbase. 4) We are storing logs in HDFS for the date which keeps track of the job 5) We run purging module to delete files from HDFS ones its loaded to HBASE ### 14. Big Data Storage **Rating:** 4.0/5.0 stars **Reviewed by:** Roshan M. | System Engineer, Information Technology and Services, Enterprise (> 1000 emp.) **Reviewed Date:** June 28, 2017 **What do you like best about Hadoop HDFS?** HDFS is fault tolerant as it makes multiple replica of the data which is stored in it, thus making it more reliable. Also when compared with traditional file systems, it is much robust and efficient in working on bulk amount of data, as it process via map reduce in the back-end. Also one of the major advantages is that HDFS can easily run on commodity hardware, making the initial setup cost very low. The commands used for HDFS to manage the files are almost the same as used in shell, providing an ease for the same **What do you dislike about Hadoop HDFS?** One of the major drawbacks of Hadoop file system is that is the amount of data to be dealt with is less, it won't be efficient, as the time for processing small data is equivalent to time taken for bulk data. By default, the security measures in Hadoop File system are disabled, making it insecure for data storage. **Recommendations to others considering Hadoop HDFS:** For those who are dealing with bulk amount of data, can surely go for hadoop file system, having offline applications, but those dealing with real time small amount of data, this is not recommended. **What problems is Hadoop HDFS solving and how is that benefiting you?** We are moving data from traditional file system to, hadoop storage, as the amount of data is increasing day by day, so we require a platform to manage this bulk data in a better manner, robust and cost efficient manner. Thus HDFS acts as the base storage for storing historic records ### 15. Hadoop distributed file system review **Rating:** 4.5/5.0 stars **Reviewed by:** Rupesh A. | system engineer, Information Technology and Services, Enterprise (> 1000 emp.) **Reviewed Date:** September 11, 2017 **What do you like best about Hadoop HDFS?** Hadoop distributed file system is a distributed,scalable,fault tolerant and very efficient data storage platform. This is used to store data and can be used to support data processing frameworks like mapreduce and Spark. The best thing about hdfs is that it can be used by multiple things to create a solution. Best thing about hdfs and hadoop framework is that for training purposes we can even create single node cluster in our laptop. **What do you dislike about Hadoop HDFS?** There are not much to dislike but speed is reduced when we deal with small files. if there are lot of small files to save then name node will be under pressure for saving the entry of those files. metadata will increase and hence performance will decrease. **Recommendations to others considering Hadoop HDFS:** HDFS is a must use solution as we have this as a complete storage solution and for now we have not found anything which can replace it as a storage solution. This can be used with spark as well as mapreduce for real time analysis as well as batch processing. we can store data by different compression techniques that is also a very good thing. **What problems is Hadoop HDFS solving and how is that benefiting you?** we are using hdfs as storage solution for large data which is got from legacy system, we use it with map reduce and spark framework to do some analysis of data. we use hbase on top of it and Also apache phoenix. it serves as storage solution by our map reduce programs to save intermediate and final outputs. ### 16. HDFS- New era File System **Rating:** 4.5/5.0 stars **Reviewed by:** prabhudayal a. | Senior Software Engineering, Information Technology and Services, Enterprise (> 1000 emp.) **Reviewed Date:** June 02, 2017 **What do you like best about Hadoop HDFS?** 1.Storing of file in sequential format, using key value pair.- Stores file as key and content as value and encrypts them. 2.128 mb block size.- Previously it was 64 which was less. But still some people like the old block size. 3.storing multiple copies of data- Store same data in multiple nodes. It helps in case there is a failure of single node. As we all know sole purpose of hdfs is using commodity hardware and make the service available. 4. Horizontal scaling and distributed architecture- This helps the system to grow without worrying about previous data. You can increase the number of nodes in case of a drastic change in the amount of data. **What do you dislike about Hadoop HDFS?** 1.Map reduce jobs takes much time for smaller amount of data too. As the map and reduce jobs are getting created for any job.- Its recommended to use relational database in case of small amount of data in range of GB 2.The immutable nature- Files in HDFS can not be altered-more specifically it can not be modified. Append is allowed though. **Recommendations to others considering Hadoop HDFS:** yes, it is recommended for bulk data **What problems is Hadoop HDFS solving and how is that benefiting you?** We have developed module to push .eml files to HDFS and store it in sequential file. The retrieval of data is much faster as compared to traditional file system. ### 17. First priority for Big Data **Rating:** 4.5/5.0 stars **Reviewed by:** Kainat R. | Chief Executive Officer, Small-Business (50 or fewer emp.) **Reviewed Date:** April 12, 2018 **What do you like best about Hadoop HDFS?** The increased block size gives hadoop advantage over others. **What do you dislike about Hadoop HDFS?** Since the block size is large, it does not perform well with data sets lesser than the block size. **What problems is Hadoop HDFS solving and how is that benefiting you?** Storing data sequentially and fetching large data sets. ### 18. Hadoop Made me Change my Major **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Insurance | Enterprise (> 1000 emp.) **Reviewed Date:** June 21, 2018 **What do you like best about Hadoop HDFS?** Easy to use, easy to read, makes a lot of sense. **What do you dislike about Hadoop HDFS?** There is nothing about hadoop I currently don't like **What problems is Hadoop HDFS solving and how is that benefiting you?** Using Agile instead of Waterfall ### 19. Big Data Storage **Rating:** 4.0/5.0 stars **Reviewed by:** Prashanth P. | System Engineer, Information Technology and Services, Enterprise (> 1000 emp.) **Reviewed Date:** June 20, 2017 **What do you like best about Hadoop HDFS?** HDFS or hadoop distributed file system is the storage component in Hadoop, where all the data resides at the end of the day. This is like a hard disk is to a computer, but actually this is a type of file system which allows user to store the data. HDFS is very cost efficient. It is also fault tolerant as it makes replica of the data which is stored in it, thus maintaining a backup of all the files in commodity hardware. **What do you dislike about Hadoop HDFS?** The major drawback of Hadoop is the lack of security measures taken, for sensitive information. This may not be considered purely for HDFS, but HDFS being a component of Hadoop, falls under this category. Also it take time in processing small amount of data, thus making it not so robust for less data as compared to bulk data. **Recommendations to others considering Hadoop HDFS:** For storing huge data, and managing this bulk data in a robust and cost efficient manner, I would surely recommend HDFS, but if the amount of data to be dealt with is less, then Hadoop File system is not recommended, as it consumes some time in processing. **What problems is Hadoop HDFS solving and how is that benefiting you?** In our business, we are moving from traditional file system to Hadoop File system, as the amount of data is growing day by day. Thus to handle this situation, we are moving to Bid Data, to manage this bulk data in a robust and efficient manner. Also the cost of installation, is very low as Hadoop works on commodity Hardware, and keeping replica of files, make it fault tolerant. ### 20. Caters to all your Data Processing Needs **Rating:** 5.0/5.0 stars **Reviewed by:** Ritwik K. | Engineering Manager, Marketing and Advertising, Mid-Market (51-1000 emp.) **Reviewed Date:** July 05, 2017 **What do you like best about Hadoop HDFS?** HDFS is inexpensive because of two reasons. Firstly, the filesystem relies on commodity storage disks that are much less expensive than the storage media used for enterprise grade storage. Secondly, the filesystem shares the hardware with the computation framework as well, in this case, MapReduce. Also, HDFS is open source and does not levy licensing fee on the user. HDFS has been around for more than 7 years and is considered mature technology. There is a large community behind it and a broad range of organizations that are storing petabytes of data on HDFS. HDFS is optimized for MapReduce workloads. It provides very high performance for sequential reads and writes, which is the typical access pattern in MapReduce jobs. **What do you dislike about Hadoop HDFS?** The main drawback of HDFS is that it is not POSIX compliant. This means HDFS is immutable, that is, files cannot be modified. **What problems is Hadoop HDFS solving and how is that benefiting you?** We have around 50 GB data getting generated per hour per colo (we operate from 4 colos). Hadoop is udes in InMobi to make sense out of this data. ### 21. Big Data Storage **Rating:** 4.0/5.0 stars **Reviewed by:** Sushant D. | System Engineer, Information Technology and Services, Enterprise (> 1000 emp.) **Reviewed Date:** June 06, 2017 **What do you like best about Hadoop HDFS?** 1.Data accessibility is very fast for huge amount of data. 2.It keeps multiple copies which makes it fault tolerance, during failure scenario. 3. It mainly uses commodity hardware, making it cost effective. **What do you dislike about Hadoop HDFS?** The major drawback is for small amount of data, as the processing which traditional system would have take for small data would be less. **Recommendations to others considering Hadoop HDFS:** I would surely recommend hadoop to people, for dealing with large amount of data. As it provides an ease, for the business solution, in a affordable price. **What problems is Hadoop HDFS solving and how is that benefiting you?** For business aspect, we are moving from old storage system to hadoop storage, as the amount of data is growing day by day, and we need a better and a feasible way to deal with this problem ### 22. Storing Bulk Data **Rating:** 4.0/5.0 stars **Reviewed by:** Dhharvi S. | System Engineer, Information Technology and Services, Enterprise (> 1000 emp.) **Reviewed Date:** June 15, 2017 **What do you like best about Hadoop HDFS?** HDFS is fault tolerance and can handle bulk data easily. Cost at the end of the day for setting up Hadoop system is less, hence leading in less cost for storing bulk data. It makes multiple copies of single data, which can be treated as a backup. **What do you dislike about Hadoop HDFS?** There are not much things for dislike, but few of them are 1. Security by default is not enabled in Hadoop system causing lac of security constrain. 2.For small data, this is not fit, as it may consume the same amount of time as for bulk data. **Recommendations to others considering Hadoop HDFS:** Only For storing bulk data, hadoop file system should be recommended. **What problems is Hadoop HDFS solving and how is that benefiting you?** Loading all the data from old file system to Hadoop ### 23. A file System of its Own **Rating:** 5.0/5.0 stars **Reviewed by:** Indrajeet S. | Design Engineer, Design, Enterprise (> 1000 emp.) **Reviewed Date:** May 31, 2017 **What do you like best about Hadoop HDFS?** The Word itself Hadoop Distributed File System, Its a file system of its own , that is it is like FAT, FAT32 NTFS or ext4 to whatever the system that we have seen, It is a file system to store the data It is better than any other storage system because of the simple fact that it does not rely on any other file system to store the data. The other things that I like is it can be increased to any extent and is capable of handling the pica bytes of data. It has capability to store and make the data available to any large resource. And the Ambari UI that is awesome to work on. **What do you dislike about Hadoop HDFS?** The only fact that it is built in java so its very complex to start working with this solution, it require huge experience to start working with Hadoop. **Recommendations to others considering Hadoop HDFS:** Yes, The name itself tells you that you should go with the solution this is the future of data analytics **What problems is Hadoop HDFS solving and how is that benefiting you?** We had a huge data base and wanted to store the digital data as well as the data stored in tables and csv. So as a future proof solution we went with Hadoop. ### 24. Its HDFS a file System of its Own. SERIOUSLY **Rating:** 5.0/5.0 stars **Reviewed by:** Suraj Kumar D. | Senior Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** May 12, 2017 **What do you like best about Hadoop HDFS?** Its a file system like NTFS,ext4,FAT32 or any of the file system you may be knowing. So now we have a filesystem for a data related activities. So it excites me more than what it does actually. It has scaled the data storage to a level where it has evolved itself a mainstore File System. **What do you dislike about Hadoop HDFS?** There is nothing that one can dislike about the product except the fact it is immensely big in size. It's a huge thing to learn and implement and to be an expert we need to dedicate ourself to this huge thing. **Recommendations to others considering Hadoop HDFS:** Should definitely implement this solution to become future proof. **What problems is Hadoop HDFS solving and how is that benefiting you?** We needed to match with the pace of the world and needed a solution for future. So that if data scales up the storage should also be able to handle it. ### 25. Hadoop Hdfs Review **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Internet | Enterprise (> 1000 emp.) **Reviewed Date:** November 09, 2017 **What do you like best about Hadoop HDFS?** Fairly intimidating at first but once you get a grip, it is easy to use. It can get complicated with all the additional functions/platforms that you can use on top of it. But I would certainly recommend the product. **What do you dislike about Hadoop HDFS?** It can get a bit intimidating and complicated with all the platforms on top of it. **What problems is Hadoop HDFS solving and how is that benefiting you?** Distributed computing and analytics. ### 26. The industry standard for open source distributed filesystems **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Computer Software | Mid-Market (51-1000 emp.) **Reviewed Date:** January 26, 2017 **What do you like best about Hadoop HDFS?** HDFS benefits from a vibrant community of passionate open-source software contributors who have made it the filesystem of choice for users trying to get fault-tolerance and performance without vendor lock-in. It also has a number of easy-to-use access points (the HDFS shell, Java API, Thrift, and REST being the most popular), which means you can reach your data through whatever means you'd like. **What do you dislike about Hadoop HDFS?** HDFS is not the easiest distributed filesystem to use and a number of design decisions made have led to some believing that it's not as performant as it could be since it tries to be everything for everyone. Look elsewhere if you have a very specific use-case as far as availability is concerned, for example. **What problems is Hadoop HDFS solving and how is that benefiting you?** My company integrates a variety of data sources through workflows that include HDFS as both a source and a destination. The vast ecosystem of access points have made it among the smoothest parts of our architecture to incorporate. ### 27. High Fault Tolerant File System **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Enterprise (> 1000 emp.) **Reviewed Date:** March 03, 2017 **What do you like best about Hadoop HDFS?** HDFS runs usually on top of commodity hardware and failure could be common. I really like fault handling feature of HDFS because it can accommodate failures and still do MAP REDUCE jobs in parallel with lightening speed. **What do you dislike about Hadoop HDFS?** Set up of HDFS is extremely painful especially dealing with all permissions and ownerships. In addition to that, there are so many products being developed nowadays and it's extremely hard to keep up with those. **What problems is Hadoop HDFS solving and how is that benefiting you?** We have developed an application which shows data map and data flow from source to target. We use HDFS to store enterprise big data and then use proprietary software on top of HDFS and Titan to achieve that. ### 28. Big data processing eith HDFS **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Enterprise (> 1000 emp.) **Reviewed Date:** September 09, 2017 **What do you like best about Hadoop HDFS?** HDFS is effective for working with large files. The command-line functionality of HDFS is straightforward and options like put, get, copy are easy to use. **What do you dislike about Hadoop HDFS?** HDFS does not support some options that other file systems support. **What problems is Hadoop HDFS solving and how is that benefiting you?** HDFS is used with Hadoop for big data processing involved with online advertising. ### 29. The Hadoop DB next level of Storage **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Enterprise (> 1000 emp.) **Reviewed Date:** February 09, 2017 **What do you like best about Hadoop HDFS?** The Scalability of the software. It can scale in both horizontally as well as vertically. the data is always available. And the ambari UI, for the UI folks who want the changes to be seen. **What do you dislike about Hadoop HDFS?** The HIVE I am unable to understand the implementation. the community support is nice but as a beginner need to spend a lot of time studying the concept **Recommendations to others considering Hadoop HDFS:** Go for it, It has everything required to save all the data **What problems is Hadoop HDFS solving and how is that benefiting you?** I am trying to create a offload repository to put thousands of records ### 30. hdfs, a mature and steady distributed storage engine **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Internet | Enterprise (> 1000 emp.) **Reviewed Date:** February 02, 2017 **What do you like best about Hadoop HDFS?** With HDFS, we can manage our data storage distributed over a cluster of ordinary machines. You data is reliabe and never loss unless you remove it. **What do you dislike about Hadoop HDFS?** HDFS is cannot be used as local data. If you want to process the data, you can only download it, or run them on MapReduce. **Recommendations to others considering Hadoop HDFS:** HDFS is reliable mature distributed storage, it the best choice. **What problems is Hadoop HDFS solving and how is that benefiting you?** Distributed storage. ### 31. Hadoop HDFS review **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Mid-Market (51-1000 emp.) **Reviewed Date:** October 31, 2016 **What do you like best about Hadoop HDFS?** HDFS is Hadoop distributed File system. The best thing I like about HDFS is reliability I get with Hadoop, its file replication is great and there are very less chance of your data being lost. To get the best benefits out of hadoop keep the file size big. At least 100MB each file. Then you will realize the power of Hadoop. Fault tolerant file system etc. **What do you dislike about Hadoop HDFS?** Its a little bit slower, but then what is not slow when you come to big file systems which work with Tera bytes of data. Even Amazon S3 is extremely slow when reading the data from it. Other than that it might be little tricky to find documentation for new users / features. **Recommendations to others considering Hadoop HDFS:** Get it from some free apache distributor. Don't try to get it from Apache directly as you might face some trivial issues **What problems is Hadoop HDFS solving and how is that benefiting you?** Mainly focussing on large scale data storage with data duplication, file redundancy, scalability etc. Used in conjunction with other big data components like Hive, Pig etc. For ETL and analytics applications. ### 32. I found HDFS stored large data sets reliably, and to stream data sets at high bandwidth was awesome **Rating:** 3.5/5.0 stars **Reviewed by:** Jonathan A. A. | General Manager, Information Technology and Services, Small-Business (50 or fewer emp.) **Reviewed Date:** April 27, 2016 **What do you like best about Hadoop HDFS?** Well...HDFS files are write once files. I consider HDFS files as write-once and read-many files. There is no concept of random writes. It is optimized for streaming access of large files. I would typically store files that are in the 100s of MB upwards on HDFS and access them through MapReduce to process them in batch mode. **What do you dislike about Hadoop HDFS?** HDFS doesn't do random reads very well. A caveat of HDFS to remember, it is a distributed file system abstracted on top of local file system by hadoop, suitable for storing huge files; however, it does not provide facility of tabular form of storage as such. **Recommendations to others considering Hadoop HDFS:** MUST UNDERSTAND! HDFS not a No-SQL. both may serve the purpose of storing huge data in distributed manner. key diff is.. In HDFS, its easier to store the data and it retrive entire row. i.e no specific key based data access. HDFS mainly for Write once and Read many. Updating in existing file in HDFS it means creating new file Few/most of the leading No-SQL support HDFS mainly -> HDFS is Distributed File System No-SQL is Data store - alternative of RDMBS **What problems is Hadoop HDFS solving and how is that benefiting you?** Trying to understand merging of files without copying them down locally using the built-in hadoop commands. Currently writing a mapreduce tool that uses the IdentityMapper and IdentityReducer to re-partition the files. Maybe I will merge all files into a single file on HDFS, run the job with just 1 reducer. If, on the other hand, I may want to partition the files into more parts, I will possibly run the job with more reducers. ### 33. A 2 Node Hadoop Cluster **Rating:** 3.5/5.0 stars **Reviewed by:** Benjamin C. | Director - Application Security, Computer Software, Mid-Market (51-1000 emp.) **Reviewed Date:** January 05, 2017 **What do you like best about Hadoop HDFS?** Setting up a 2 node Hadoop cluster was easy. We just used it as a distributed storage medium. **What do you dislike about Hadoop HDFS?** What is the hype behind this? One could easily set up a 2 node HDFS and say a product was conformant. **What problems is Hadoop HDFS solving and how is that benefiting you?** Business problems are showing compatibility with HDFS, to show that data can be stored in HDFS, in Oracle, in mysql. ### 34. Very rich ecosystem and is there to stay **Rating:** 4.5/5.0 stars **Reviewed by:** kapil c. | SDE-I, Internet, Enterprise (> 1000 emp.) **Reviewed Date:** March 20, 2016 **What do you like best about Hadoop HDFS?** All type of tool on top of HDFS like pig/hive (help to reduce your time in writing MR jobs) ,sqoop (to transfer data from RDBMS <-> hdfs) ,NOSQL db can use as their storage FS(ex. HBASE) and many more are available currently plus many big -big organization(cloudera ,MAPR ,hortonwork to name a few) are actively contribution in hdfs ecosystem . **What do you dislike about Hadoop HDFS?** For beginner/First timer is a bit difficult to set up hdfs in cluster mode and currently hdfs use yarn2 as their resource manager which is develop keeping very narrrow thinking .They can enhanced by looking at MESOS. Every stage data (intermediated result ) store in disk , for streaming processing hdfs is the worst choice. **Recommendations to others considering Hadoop HDFS:** 1. for streaming processing ,dont even look at this. 2.setup and maintain is quite difficult 3.ecosystem is great and community is active adding good feature on top of hdfs. **What problems is Hadoop HDFS solving and how is that benefiting you?** I have to develop a rich analytical dashboard for our business client . The benefits: 1. For the batch processing with fault tolerant feature its simply the best. 2. Spring integration with hadoop no problem at-all. 3. we have to use column based NOSQL db HBASE to support as dashboard analytic and HBASE on top hdfs work like charm . ### 35. Robust, Easy to Manage, Distributed FileSystem for Hadoop Applications **Rating:** 4.0/5.0 stars **Reviewed by:** Edward S. | Software Engineer/Manager, Computer Networking, Enterprise (> 1000 emp.) **Reviewed Date:** March 15, 2016 **What do you like best about Hadoop HDFS?** Automatic replication, stable, compatible with/required for the rest of the Hadoop ecosystem. Its pretty easy to manage. Rack Awarenes ensures that losing a single rack doesn't result in the loss of data. Overall, its kind of an awkward thing to write a review about since, it is really an enabling-technology. However, when combined with an analytical tool that can take advantage of HDFS (like Map/Reduce, Hive, Pig, etc), HDFS shows its value. I'm also not aware of any alternatives to using HDFS with these tools. **What do you dislike about Hadoop HDFS?** Its purpose-built for Hadoop, and large-scale data processing. That said, it doesn't really work well as a general-purpose filesystem. You can mount it with NFS, but realize that as bad as NFS is, NFS on HDFS is worse. Don't get caught in this trap. For the most part, stick to interacting with it using Hadoop's tools, not generic filesystem tools over NFS. **Recommendations to others considering Hadoop HDFS:** Its basically a requirement for Hadoop Map/Reduce, Hive, Pig, and many other tools in the Hadoop ecosystem. Don't replace your SAN with HDFS, however, as there are key features which are missing for that purpose. **What problems is Hadoop HDFS solving and how is that benefiting you?** Large scale data processing. HDFS enables Hadoop to bring the code to the data as opposed to shipping the data to the code (like a massive DB server that has storage arrays). Redundancy and Scale. ### 36. 6 Years On, Hadoop Is Still the Big Data Platform to Beat **Rating:** 4.5/5.0 stars **Reviewed by:** James O. | Senior Lead Technologist, Management Consulting, Enterprise (> 1000 emp.) **Reviewed Date:** March 14, 2016 **What do you like best about Hadoop HDFS?** After working with Hadoop for 6 years, I like the direction in which it has evolved. It started as a tightly-coupled offering of a distributed data platform (HDFS) and an analytics processing framework (MapReduce); however, it has since expanding its scope tremendously. After the initial success of MapReduce, it has become quite clear that it has many limitations as an algorithm. Other frameworks such as Apache Spark have far surpassed its capabilities. Seeing that trend, the Hadoop team instead chose to focus on Hadoop as a base platform for dozens of data and analytics offerings. This lead to the strengthening of the already robust HDFS and the creation of YARN as an applications framework. This gives the Hadoop platform a lot of widespread appeal and makes it a great basis for any big data processing platform. Many tools exist for quickly standing up entire Hadoop clusters in very little time, and it treats scaling and fault tolerance as primary as first-order priorities. **What do you dislike about Hadoop HDFS?** There are two major areas that Hadoop could use improvement that have existed since the beginning and continue to be a problem for the implementation of Hadoop in real world settings. The first is poor documentation on performance and tuning. Hadoop works fairly well out of the box, but once you start to encounter problems there are very scarce resources on trying to troubleshoot those issues. Hadoop has been around long enough as an open source project that common configuration strategies and troubleshooting techniques should be built into the documentation. Secondly, and more importantly for many users, are the lack of security options for Hadoop. There are few if any built-in options, and any plugable solutions are fairly difficult to implement. **Recommendations to others considering Hadoop HDFS:** Hiring experienced DevOps talent is more essential than analytic developers. The skills for analytic developers can be trained faster than those of skilled DevOps team members. **What problems is Hadoop HDFS solving and how is that benefiting you?** I have mostly been focused on large-scale analytic workflows for our clients. We have utilized Hadoop and its ecosystem components like Hive, Pig, Spark, Flume, Oozie, and others to implement scaleable workflows for ETL and analytic applications. Hadoop enables the scale and reliability that is an absolute requirement of our customers. We have also used Hadoop as a basis for streaming analytics using YARN and Spark for real-time data analysis. ### 37. Hadoop Review **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Internet | Enterprise (> 1000 emp.) **Reviewed Date:** March 08, 2016 **What do you like best about Hadoop HDFS?** I like MapReduce code a lot. Mappers and Reducers and how the overall hierarchy goes by. Hadoop is a platform that I have chosen a year ago and still I am in love with it because of it's simplicity for solving complex problems involving very large database. I also did Apache Giraph which goes into graph processing and was a great experience learning a whole new product of Hadoop. I like solving real life challenges using Hadoop like predicting earthquakes so that the results could be less devastating. This is one of my proposed ideas but there are many more like these which I like a lot. **What do you dislike about Hadoop HDFS?** I dislike the numerous products that are developing in Hadoop architecture because a developer can never learn all the products based on hadoop. He/She can learn only a few ones which are used in a very extensive way. So why not integrate other less used products in the mostly used products so that it gets the added functionality. **Recommendations to others considering Hadoop HDFS:** If you consider switching to Hadoop platform, in the learning phase, don't setup hadoop from scratch. Instead concentrate on your learning and download the pre installed hadoop virtualbox image of cloudera or hortonworks or MapR etc. I took me around a month to fully configure single node and multi node because I implemented them from scratch. Had I used the above mentioned virtual images, it would have helped me a lot and save my time as well. **What problems is Hadoop HDFS solving and how is that benefiting you?** Actually I was into learning Big Data and Hadoop but soon I fell in love with it. Recently I did a project on it by reviewing the big sales data of NY stores and processing Udacity's DIscussion forums which is a great way to analyze data and give all the statistics. ### 38. I'm a BigData architect with 6 years experience in building Hadoop based infrastructure **Rating:** 4.5/5.0 stars **Reviewed by:** David G. | Chief Software Architect, Computer Software, Small-Business (50 or fewer emp.) **Reviewed Date:** March 10, 2016 **What do you like best about Hadoop HDFS?** It's currently the best distributed file system for implementing biodata projects. The main reason rely on the fact that HDFS is fully integrated with many parallel computing platforms for doing BigData analysis: Map/Reduce, Spark, Impala, Drill. It's very mature, stable and really robust, optimised for streaming data to the application layer. It provides now a full support for security, Posix-like, Posix ACLS and support for directory based encryption. **What do you dislike about Hadoop HDFS?** It works very badly with many small files. HDFS is optimised for dealing with a relatively small number of files but very big. This is an annoying limitation that forces many architectural decisions for supporting the data ingestion effectively. **What problems is Hadoop HDFS solving and how is that benefiting you?** We solve problem of data science on huge amount of data. HDFS as part of the bigger Hadoop eco-system provides all the pieces for ingesting/transform and analyse vas amount of data using advanced parallel platforms. ### 39. Good **Rating:** 5.0/5.0 stars **Reviewed by:** Udita P. | Software Development Engineer, Internet, Enterprise (> 1000 emp.) **Reviewed Date:** July 21, 2016 **What do you like best about Hadoop HDFS?** It is quick and perform well with small clusters too. I used it to implement my thesis. Could be a little challenging if u not aware with linux **What do you dislike about Hadoop HDFS?** The debugging and logging is not very user friendly. Although it has a decent interface for job tracking. **What problems is Hadoop HDFS solving and how is that benefiting you?** I used it for my thesis. Scaling is easy. It can be used for lot of big data processing requirements ### 40. Hadoop HDFS is mature solution for storing and processing big data if used in right way. **Rating:** 3.5/5.0 stars **Reviewed by:** James C. | CTO & VP of Research & Development, Computer Software, Mid-Market (51-1000 emp.) **Reviewed Date:** March 14, 2016 **What do you like best about Hadoop HDFS?** Hadoop HDFS is proven scalable and stable enough for big data processing. I have over 6 years in product development and operation on HDFS. Storing and processing terabytes scale data with HDFS. Hadoop HDFS handles scale problem well and most of problem can be solved. **What do you dislike about Hadoop HDFS?** HDFS is optimized for big file and batch oriented data process. User should really need to pay attention on "Small File Problem", avoiding produce large amount of small files. This will eventually kill HDFS. **What problems is Hadoop HDFS solving and how is that benefiting you?** We use HDFS to store web logs for recommendation system, Call Details Record of carrier and device log of Hi-Tech manufacture. The benefits of HDFS is it's scalability and relative lower cost of storing data and be able to leverage MapReduce, Hive, Impala and Spark for further data analysis. ### 41. HDFS is effective for long time storage **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Mid-Market (51-1000 emp.) **Reviewed Date:** January 27, 2017 **What do you like best about Hadoop HDFS?** it is effective for long time storage, and easily scalable. **What do you dislike about Hadoop HDFS?** Writing to HDFS system is a little bit slow. **Recommendations to others considering Hadoop HDFS:** Most effective for data warehouse as it is cheap and easily scalable. **What problems is Hadoop HDFS solving and how is that benefiting you?** Use HDFS as data warehouse. Reliable for long time storage. ### 42. An essential primary tool for distributed programming and data management **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Small-Business (50 or fewer emp.) **Reviewed Date:** March 18, 2016 **What do you like best about Hadoop HDFS?** HDFS supports features such as partitioning and replication that are actually mandatory to be present in a distributed environment. Of course, many optimizations should be done over the next years but the main concept will be always the same. Move code into the data and keep your data safe with no risk depending on the failures. What I like best in HDFS is the user interface which is pretty similar to a common local Linux filesystem. Moreover, HDFS is very compatible and that can be integrated with the majority of the frameworks that are used today like Hadoop and Spark. Last but not least, HDFS is open source and a huge community supports it. **What do you dislike about Hadoop HDFS?** HDFS has some disadvantages as well. First of all, I would really like it to be more customizable and to provide more features to the user interface. By doing this, users will be free to play and experiment with new ideas which will be integrated with HDFS. I also have observed that someone has to be an expert in order to use it securely in his application and there is no much documentation about how to achieve this specifically in HDFS. **Recommendations to others considering Hadoop HDFS:** There are a lot of systems that someone can do his job but HDFS would be always the most open one. It is also a very good choice for someone who is completely unexperienced with distributed programming because there is a lot of documentation on the Internet. **What problems is Hadoop HDFS solving and how is that benefiting you?** The most common problem that I am trying to solve is the big data management and the application of plenty of algorithms to this kind of data. I am currently also trying to integrate it with a new architecture that I am working on. ### 43. Good enough but not state of the art anymore (compare to Spark) **Rating:** 3.5/5.0 stars **Reviewed by:** Aleksey I. | Platform Architect, Health, Wellness and Fitness, Mid-Market (51-1000 emp.) **Reviewed Date:** March 22, 2016 **What do you like best about Hadoop HDFS?** Distributed and fault tolerant, transparent. Mimics Unix FS features which are familiar to many users. Good fit for tech savvy users (config files, command line interface). Fast enough. **What do you dislike about Hadoop HDFS?** Not as fast as your local FS. More limited in tools and features than your familiar Unix environment. Bad fit for non-tech savvy users (config files, command line interface). Not entirely POSIX compliant, but gains in performance because of that. **Recommendations to others considering Hadoop HDFS:** Well supported and understood solution at the moment. Consider other Spark based options if possible. **What problems is Hadoop HDFS solving and how is that benefiting you?** Computing large datasets and storing files for input into map/reduce. It simplifies the process quite a bit - no need to worry about replication and fault tolerance. ### 44. HDFS for logs storage **Rating:** 3.5/5.0 stars **Reviewed by:** Shulhi S. | Software Developer, Computer Software, Small-Business (50 or fewer emp.) **Reviewed Date:** March 14, 2016 **What do you like best about Hadoop HDFS?** Distributed file storage made easy with using HDFS. I don't need to know where the files are stored physically in the server because HDFS exposed all the files as if it was a single storage with multiple backup (depending on you replication factor). In term of using HDFS API, it is straight forward to use. **What do you dislike about Hadoop HDFS?** Configuration. To get HDFS running might be easy or complicated depending on your experience. We are using Hadoop together with Cloudera, so that was really easy for us to get things started. However, as any other Hadoop components, fine tuning HDFS can be tricky. Debugging HDFS can also be tricky, like suddenly HDFS doesn't allow write due to it was in safe mode. At the point I was using Hadoop, getting Hadoop to work with HA is also challenging, namenode was a single point of failure. HDFS also doesn't work well with lots of small files. For average user, it can be daunting for them to access HDFS (I think HDFS has web app running with limited functionality), for developers it would be no issue. **Recommendations to others considering Hadoop HDFS:** HDFS is a great tool if you're looking for proven solution for file storage that offers distributed storage and file backups. However, HDFS is just a file system and nothing more than that. I've got clients who think HDFS is like magic, put up files into HDFS and come out analytic. Hadoop is prone to failure, having someone who knows Hadoop in and out is great plus. **What problems is Hadoop HDFS solving and how is that benefiting you?** I was building internal tool for managing logs and analyzing logs for business intelligence. We used logs as our source to train machine learning algorithm to detect system failure. ### 45. Hadoop HDFS **Rating:** 3.5/5.0 stars **Reviewed by:** Verified User in Transportation/Trucking/Railroad | Small-Business (50 or fewer emp.) **Reviewed Date:** March 14, 2016 **What do you like best about Hadoop HDFS?** It is a good way to make big storages and for distributed system. **What do you dislike about Hadoop HDFS?** I don't know much about Hadoop HDFS. But If I have to answer the question then, It is hard to use whenever I wanted to control some files or directories. Commands are not comfortable for me. I wanted to use like Linux command. This is a little bit different with Linux's, I think. **Recommendations to others considering Hadoop HDFS:** Hadoop HDFS is a good solution for distributed and large scale data when if you had to control big data for text mining or data mining using machine learning like things. **What problems is Hadoop HDFS solving and how is that benefiting you?** My company is related with data mining and machine learning using social data and etc. Some project needed to prediction from that data for making prediction models. So We decided to make that using Hadoop ecosystem. Finally, We achieved the project using Hadoop and Map & Reduce function. and I realized that it could be a pretty good solution. ### 46. Hadoop is a tool with both bitterness and sweet **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Higher Education | Enterprise (> 1000 emp.) **Reviewed Date:** March 08, 2016 **What do you like best about Hadoop HDFS?** Hadoop is a collection of software that handles distributed file system (HDFS), and distributed processing mechanism on top of it (MapReduce). It is highly scalable and reliable. With Hadoop, users could specify their processing requirements on large datasets without worrying the details of underlying communication and data distribution. Hadoop can scale up easily to adapt to workflow increase. Automatic data replication mechanism in HDFS guarantees its reliability. **What do you dislike about Hadoop HDFS?** Hadoop is written in Java and it is not fast. It cannot handle the data processing requests in real-time. Its processing layer, MapReduce, simplifies the processing logic by supporting only a Map and Reduce function, but it also introduces inconvenience to express complicated processing logic. Hadoop adopts master-slave architecture, but the master is designed in single-node mode: when the master node is down, it is difficult to get recovered. Users have to purchase high-end hardware to prevent master-node failures. **Recommendations to others considering Hadoop HDFS:** If you have data that are large in size, use Hadoop. The initial setup and trial is simple; and you can figure out easily whether it is a good solution to your data processing requirements. Why not give it a try? But hadoop is not a solution for all big data problems. It cannot handle interactive, iterative, and real-time processing well. **What problems is Hadoop HDFS solving and how is that benefiting you?** By using Hadoop, we can explore much larger datasets and find the hidden essence in them in order to provide better service. The cost of developing, debugging, and deploying of the tools becomes easier than before, and the scale of processing is expanded significantly. ### 47. I am using hadoop-hdfs in bioinformatics for human genome data **Rating:** 4.5/5.0 stars **Reviewed by:** 宗 . | Technique Consultant, Biotechnology, Small-Business (50 or fewer emp.) **Reviewed Date:** March 14, 2016 **What do you like best about Hadoop HDFS?** hdfs is high avalible and scalable, I can expand the storage only add several datanodes. And with hdfs genome data can be easily analyzed by mapreduce. **What do you dislike about Hadoop HDFS?** hdfs is not so good for small files, and the nfs-gate-way is also not very well. **Recommendations to others considering Hadoop HDFS:** I think hadoop has a very good community, although hdfs still has some bugs(I think hadoop-yarn make have more bugs, espically on dokcer-container-executor), I think it will be better. **What problems is Hadoop HDFS solving and how is that benefiting you?** When using java, It is not so easy to manipulate files in hdfs by hadoop api. I find an open-source project jsr203-hadoop(https://github.com/damiencarol/jsr203-hadoop) can make things simple. One can read and write hdfs files via NIO api in jdk1.7. But at that time I found a small bug in the project when I tring to move a file. I fixed the bug and the auther (damiencarol) kindly merged my code. ### 48. Hadoop Easy Distributed **Rating:** 4.0/5.0 stars **Reviewed by:** Anshorimuslim S. | Platform Developer, Information Technology and Services, Small-Business (50 or fewer emp.) **Reviewed Date:** March 14, 2016 **What do you like best about Hadoop HDFS?** Well I am using Hadoop HDFS for HBase filesystems. I found it's really easy to deploy. I use Cloudera Manager as hadoop package, it could be more easy. If you have a lot of nodes, then truly you will have power from Hadoop HDFS **What do you dislike about Hadoop HDFS?** It's quite troblesome for tuning HBase and HDFS. At first when we have fe w nodes it doesnt looks better, but when we hit more nodes, performance gained. But still, lot of tinkering to do. **Recommendations to others considering Hadoop HDFS:** Use a good package, don't use bare install **What problems is Hadoop HDFS solving and how is that benefiting you?** Social Media monitoring and analytics ### 49. Hadoop Cluster Usage **Rating:** 4.0/5.0 stars **Reviewed by:** Timothy S. | Principal Developer Advocate, Enterprise (> 1000 emp.) **Reviewed Date:** January 07, 2016 **What do you like best about Hadoop HDFS?** Hadoop is a no brainer for big data. The main killer feature is HDFS. Having a redundant WORM file system is amazingly useful. There's a reason Google invented in and Yahoo made it open source. 3 copies of your file just works. Cheap commodity servers, but still fast and stable. Never lose data, store everything. Access and use in multiple use cases. So many tools and other projects around Hadoop make it a must have for all enterprises and startups. You add Spark which most distributions include and you can pretty much do everything you need. Ambari and Hue make it easy to setup now. **What do you dislike about Hadoop HDFS?** There's a lot of stuff in Hadoop, also there's always 10 ways to do something and hard to know what's the best. Do you do Storm or one of 20 other frameworks. Should I store in Parquest, ORCFile, Avro or CSV or something else? Do you compress with SNAPPY or nothing. What level of encryption? Is Kerberos good enough for my security. Security is a bit lax and there's definitely a lot of things to configure. **Recommendations to others considering Hadoop HDFS:** Try it out in one of the sandboxes. It's very easy to install with Ambari. The sandboxes are all setup and running with all the basic tools. Try the HDFS CLI and copy a few files into HDFS. Then try to access them through the CLI and through some basic HiveQL. It's easy to load, transform and query your data. Easy to pull it out of SQL and drop it in HDFS. The only hard part is to figure out what tools to use for BI and for imports. **What problems is Hadoop HDFS solving and how is that benefiting you?** Storing everything, accessing everything, not losing data and rapid access to big and fast data. It's great for BI and for applications. ### 50. Solid, scalable solution **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Computer Games | Mid-Market (51-1000 emp.) **Reviewed Date:** March 16, 2016 **What do you like best about Hadoop HDFS?** HDFS is reliable and solid, and in my experience with it there are very few problems using it. If you have your own data centre and you use Hadoop, it's the obvious choice for reliably storing your data. **What do you dislike about Hadoop HDFS?** If your NameNodes all go down, then HDFS is pretty much useless as you won't know which file blocks are where and which files they belong to -- and I've read it's difficult to recover (or impossible) if you completely lose your NameNode file mappings. Fortunately I've never personally seen this occur. **Recommendations to others considering Hadoop HDFS:** Again, you get it for free if you have your own Hadoop installation and run your own datacentre, so you might as well use it for archiving/storage/input to various ETL. Even if you're "in the Cloud" you usually have access to HDFS, even ephemerally, and it's quicker to do work on it directly than some systems such as Amazon S3 (of course you still need to persist your data back off of HDFS when you're done in such a situation). **What problems is Hadoop HDFS solving and how is that benefiting you?** HDFS is used for MapReduce processes, Hive tables, Spark job input, for backing up data... The list goes on. You get replication for free, which is also very useful. ## Hadoop HDFS Discussions - [What is Hadoop HDFS used for?](https://www.g2.com/discussions/what-is-hadoop-hdfs-used-for) - 1 comment, 1 upvote - [View Hadoop HDFS pricing details and edition comparison](https://www.g2.com/products/hadoop-hdfs/reviews?page=2§ion=pricing&secure%5Bexpires_at%5D=2026-08-02+10%3A58%3A13+-0500&secure%5Bsession_id%5D=cf920c73-4dae-4173-8599-2c3d2eb6c0f0&secure%5Btoken%5D=37ce6dec560f8cbc96dc210d03beb3dcbd7a41ef6c3eacd80e36f962b2f3e570&format=llm_user) ## Hadoop HDFS Integrations - [Hive](https://www.g2.com/products/hive-hive-hive/reviews) - [Spark](https://www.g2.com/products/apache-spark/reviews) ## Hadoop HDFS Features **Database** - Real-Time Data Collection - Data Distribution - Data Lake **Integrations** - Hadoop Integration - Spark Integration **Platform** - Machine Scaling - Data Preparation - Spark Integration **Processing** - Cloud Processing - Workload Processing **Building Reports** - Data Transformation - Data Modeling - WYSIWYG Report Design - Integration APIs **Platform** - Mobile User Support - Customization - User, Role, and Access Management - Internationalization - Sandbox / Test Environments - Performance and Reliability - Breadth of Partner Applications ## Top Hadoop HDFS Alternatives - [Databricks](https://www.g2.com/products/databricks/reviews) - 4.6/5.0 (1,327 reviews) - [Google Cloud BigQuery](https://www.g2.com/products/google-cloud-bigquery/reviews) - 4.5/5.0 (1,144 reviews) - [Cloudera](https://www.g2.com/products/cloudera/reviews) - 4.1/5.0 (131 reviews)