# 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 find HDFS excels at **storing large files reliably** with excellent fault tolerance, especially for batch workloads. (1 reviews) - Users appreciate the **solid data security** and fault tolerance of Hadoop HDFS, ensuring reliable storage across multiple machines. (1 reviews) - Users value the **robust data storage** capabilities of HDFS, ensuring reliable performance for large files across systems. (1 reviews) - Users value the **ability to store large datasets** across multiple machines with excellent fault tolerance and stability. (1 reviews) **What users dislike:** - Users note the **increased costs** for managing HDFS, requiring dedicated resources for maintenance and scaling challenges. (1 reviews) - Users find that **maintenance issues** with HDFS require extensive resources and dedicated teams for effective management. (1 reviews) - Users find **performance issues** with HDFS, especially when handling small files and managing clusters becomes burdensome. (1 reviews) - Users criticize HDFS for its **poor performance** , struggling with scalability, management, and efficiency in modern environments. (1 reviews) - Users express concerns about **security issues** with HDFS, highlighting the need for dedicated teams for management and maintenance. (1 reviews) ## Hadoop HDFS Reviews ### 1. HDFS: Reliable, But Definitely Showing Its Age **Rating:** 3.0/5.0 stars **Reviewed by:** Abhishek K. | Technical Lead, Information Technology and Services, Enterprise (> 1000 emp.) **Reviewed Date:** August 01, 2025 **What do you like best about Hadoop HDFS?** HDFS still does one thing really well store large files across multiple machines with solid fault tolerance. It’s great for batch workloads and works like a charm when paired with Spark, Hive, or traditional Hadoop jobs. Once you’ve set it up right, it’s stable and does its job quietly in the background. For old school, on prem big data pipelines, it’s a dependable workhorse. **What do you dislike about Hadoop HDFS?** Let’s be real, HDFS is not keeping up with the times. In today’s world of cloud-native, serverless, auto-scaling storage, HDFS feels like using a Nokia in an iPhone world. Scaling means more hardware, more headaches. Managing NameNode/SecondaryNameNode is like babysitting one wrong move and your cluster throws a tantrum. It handles large files well, but feed it too many small files and it chokes. It also lacks the flexibility and cost efficiency of cloud storage, no managed service feel, and don’t even ask about object-level access. Security, upgrades, and maintenance? A whole job in itself. You’ll end up needing a dedicated team just to keep things smooth. **What problems is Hadoop HDFS solving and how is that benefiting you?** Storing large batch data in older pipelines Running PySpark jobs on top of Hadoop clusters Transitional layer before moving data to cloud-based systems like GCS or S3 ### 2. My experience with Hadoop **Rating:** 5.0/5.0 stars **Reviewed by:** Varad V. | AI/ML Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** January 24, 2024 **What do you like best about Hadoop HDFS?** The most that I like about hadoop is that it is extremely easy to use and implement. I work with big data and storing that is most convenient with hadoop. Transforming and modelling data is easy with hadoop. The scalability feature of it helps me store large amount of data quickly whenever needed. Due to parallel processing, it is quite fast. **What do you dislike about Hadoop HDFS?** The only bad thing about Hadoop is that is doesn't allow real time processing of data like some other distributed file and storage systems. **What problems is Hadoop HDFS solving and how is that benefiting you?** Hadoop helps me store large amounts of data for analysing purpose efficiently. That makes it useful for predictive analysis, data modelling and transformation that I have to do from time to time. I personally have to work only with historical data and not real time data, so Hadoop HDFS is my go to data storage system. ### 3. Compatibility for large/high volume **Rating:** 4.5/5.0 stars **Reviewed by:** Mohammad Mateen M. | Software Developer, Small-Business (50 or fewer emp.) **Reviewed Date:** March 06, 2024 **What do you like best about Hadoop HDFS?** It helps in managing large amount very easily.as someone who uses Mssql server exploring and working with Hadoop Hdfs was very good and it gives a new exploration to your knowledge so very good and efficient overall. **What do you dislike about Hadoop HDFS?** So far the process has been convenient, of course as a beginner if you miss something that could cause problem like understanding hdfs could be difficult but if taken care once then it is obvious that process goes smoothly. **What problems is Hadoop HDFS solving and how is that benefiting you?** So as we can create HDFS clusters, it has helped in the storing and analysing large volume of data more efficiently and more efficient means more time saving ### 4. HDFS for big data storage **Rating:** 5.0/5.0 stars **Reviewed by:** Nitish K. | Big Data Engineer, Computer Software, Small-Business (50 or fewer emp.) **Reviewed Date:** October 17, 2023 **What do you like best about Hadoop HDFS?** Hadoop's storing of large amount of data into a clusters that makes data as fault tolerant, secure and faster processing and scalability **What do you dislike about Hadoop HDFS?** There is nothing i disliked about HDFS but it's not easy to access, one must learn and install about hadoop to use hdfs, it could be better if there is a special user interface to store data using hdfs directly **What problems is Hadoop HDFS solving and how is that benefiting you?** HDFS helped with storing of 100's of GB's of data into hadoop HDFS cluster ### 5. I was a total good experience to go through with the huge chunk of data and dealing with it. **Rating:** 4.5/5.0 stars **Reviewed by:** Himani K. | Senior Analyst, Enterprise (> 1000 emp.) **Reviewed Date:** June 07, 2023 **What do you like best about Hadoop HDFS?** It helps to deal with huge amount of data in a very smooth way, and it also got many tools which make it more and more productive to deal with, it has gave a whole new and good approach to Deal with the company's data. **What do you dislike about Hadoop HDFS?** You can say it got many tools for each and every new approach in the Hadoop but it also sometimes get hectic to work with data, it need different tool to apply in every part of the analysis of the data. **What problems is Hadoop HDFS solving and how is that benefiting you?** It is slowing one biggest problem we used to face in the technology world which is dealing with the huge amount of data how to store it when you don't have that much space to store that but Hadoop solved it. ### 6. Great tool to handle large data **Rating:** 4.0/5.0 stars **Reviewed by:** Ajeet M. | Software Engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** June 14, 2023 **What do you like best about Hadoop HDFS?** Large volumes of data can be handled easily with Hadoop HDFS, which can scale as your needs change. Even in the face of failures, it guarantees that data is consistently accessible and trustworthy. Hadoop HDFS is a flexible solution that works well with other tools in the Hadoop ecosystem due to its low-cost architecture and capacity to process many sorts of data. **What do you dislike about Hadoop HDFS?** There are issues with Hadoop HDFS to think about. For multiple little files, it causes delays and lags a bit. There are limits to real-time tasks. Hadoop HDFS configuration and management can be challenging, and data replication increases the need for storage. **What problems is Hadoop HDFS solving and how is that benefiting you?** Hadoop HDFS benefits me by solving business problems in the following ways: 1) It facilitates effective data storage of significant amounts. 2) It enables parallel processing, enabling sophisticated analytics and insightful information. 3) It uses strategies for fault tolerance to guarantee data availability and dependability. 4) Compared to specialised systems, it is more affordable and easily scales to address expanding data needs. ### 7. Hadoop HDFS Review **Rating:** 4.0/5.0 stars **Reviewed by:** Abhishek S. | Senior Software Engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** June 06, 2023 **What do you like best about Hadoop HDFS?** One of the things I like best about Hadoop HDFS is its ability to handle massive amounts of data across multiple nodes. It is designed to distribute data and processing tasks, making it highly scalable and fault-tolerant. Another great feature is its fault recovery mechanism, which ensures data availability even in the event of node failures. Additionally, Hadoop HDFS provides a simple and efficient way to store and retrieve data, making it a popular choice for big data processing and analytics. **What do you dislike about Hadoop HDFS?** Firstly, HDFS can have relatively high latency for small file operations due to the overhead of storing metadata. Secondly, its reliance on Java may pose difficulties for developers accustomed to other programming languages. Thirdly, Hadoop HDFS lacks built-in support for fine-grained access control, requiring additional configuration for robust security measures. Additionally, the complexity of configuring and managing HDFS clusters can be a learning curve for newcomers. Lastly, Hadoop HDFS might not be the ideal choice for real-time data processing scenarios due to its batch-oriented nature. **What problems is Hadoop HDFS solving and how is that benefiting you?** Hadoop HDFS solves the problem of storing and processing massive amounts of data by providing a distributed file system. This allows for horizontal scalability and fault tolerance, enabling efficient handling of big data workloads. With HDFS, you can store and analyze vast datasets across multiple nodes, utilizing the power of parallel processing. The benefits include improved data availability, faster data processing, and the ability to scale your infrastructure as your data grows. Ultimately, Hadoop HDFS empowers organizations to extract valuable insights from their data, leading to better decision-making and competitive advantage ### 8. Brief Review of HDFS **Rating:** 4.0/5.0 stars **Reviewed by:** Karan S. | Senior Consultant Big Data Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** June 06, 2023 **What do you like best about Hadoop HDFS?** HDFS High Throughput perfectly designed to store, analyse, and stream huge files and data. With its emphasis on sequential read and write operations, large throughput rates are possible. Due to this, HDFS is a good choice for workloads that require a lot of data and batch processing. **What do you dislike about Hadoop HDFS?** Hadoop HDFS offers simple access control techniques, however in some business circumstances, these might not be enough. It may be necessary to perform additional configuration and management for advanced security features like fine-grained access control, encryption, and integration with external security systems in matter of Security and access control. **What problems is Hadoop HDFS solving and how is that benefiting you?** HDFS includes built-in fault tolerance methods to assure data availability. By replicating data across numerous data nodes, HDFS guards against data loss in case of hardware failures or other node problems. Data replication and recovery are automatically handled by the system, ensuring that access to data is maintained even in the event of failures which basically helped me to complete some my tickets. ### 9. Hadoop HDFS: A Scalable and Reliable Solution for Storing and Processing Big Data **Rating:** 4.5/5.0 stars **Reviewed by:** Archit M. | Market Risk Analyst, Enterprise (> 1000 emp.) **Reviewed Date:** June 07, 2023 **What do you like best about Hadoop HDFS?** Hadoop HDFS can be easily scaled out to handle larger amounts of data. This is done by adding more nodes to the Hadoop cluster.It has also many features such as native support to large dataset, higher fault tolerance and it can also provide high throughput data access. **What do you dislike about Hadoop HDFS?** HDFS has limitations such as it is not suitable for large datasets, slow processing speed and no real time processing, higher latency. But overall it is a good experience. **What problems is Hadoop HDFS solving and how is that benefiting you?** Hadoop HDFS is solving a big problem of Big data by storing the data in distributed form in different machines. There are huge amount of data present and that data have to be store in a cost effective way and process it efficiently. And Hadooo is doing exactly the same ### 10. Hadoop HDSF Review **Rating:** 4.0/5.0 stars **Reviewed by:** Divyanshi S. | Cloud Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** June 07, 2023 **What do you like best about Hadoop HDFS?** Hadoop file system is way better than traditional file system in many ways. It has many features like native support of larger datasets, higher fault tolerance and it can also provide high throughput data access for applications having large scale data sets. **What do you dislike about Hadoop HDFS?** There are few limitations of HDFS like it is not suitable for small datasets, slow processing speed, no real time data processing, bit harder to use, latency is bit higher. But overall good experience. **What problems is Hadoop HDFS solving and how is that benefiting you?** Hadoop HDFS is solving a big problem of Big data by storing the data in distributed form in different machines. There are huge amount of data present and that data have to be store in a cost effective way and process it efficiently. And Hadooo is doing exactly the same. ### 11. Fast Easy and effective tool for your business **Rating:** 5.0/5.0 stars **Reviewed by:** vimal k. | Dotnet Developer, Mid-Market (51-1000 emp.) **Reviewed Date:** June 09, 2023 **What do you like best about Hadoop HDFS?** It is a most powerful and scalable framework for big data processing and storage. Its distributed nature and MapReduce model enable us perform any bussiness logic with faster and effective performance. **What do you dislike about Hadoop HDFS?** However, The configurations can take time when you start setting up in your system Additionally, Hadoop's MapReduce model may not be the most efficient approach for certain types of data processing tasks, particularly those requiring real-time or interactive analysis. But most of the time it can provide you the best results. **What problems is Hadoop HDFS solving and how is that benefiting you?** I have used hadoop to solve various problems including sports, companies, educational data. it has proven to be the one of the best tool which i have used to filter various fields in my data. ### 12. My experience with Hadoop HDFS **Rating:** 5.0/5.0 stars **Reviewed by:** Sahiti G. | Software Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** June 06, 2023 **What do you like best about Hadoop HDFS?** I appreciate the high data availability of data and data processing speed. There is no latency compared to other file systems; you don't need to worry about node failures. I am one of the early users of HDFS, and the features that it has grown are amazing making the system wholistically more robust **What do you dislike about Hadoop HDFS?** Lack of real-time analysis. We need extensive processing and data cleaning before we can do any analytics. It would have been great if there was some intelligence that would allow at least a high level of analytics **What problems is Hadoop HDFS solving and how is that benefiting you?** Data processing in parallel manner to handle large amount of data to generate our financial reports while meeting the ETAs ### 13. Hadoop-Hdfs **Rating:** 4.0/5.0 stars **Reviewed by:** Abhishek S. | Openshift Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** June 07, 2023 **What do you like best about Hadoop HDFS?** hadoop hdfs was developed using file system design. which holds large amount of data and provide easily access. hadoop store huge data, file which stored accross multiple machine. this is the best about hadoop hdfs **What do you dislike about Hadoop HDFS?** their is nothing to dislike. i would recommend Hadoop hdfs to enterprise. hadppp hdfs is best solution for enterprise. it is enterprise grade solutions their is nothing to dislike. **What problems is Hadoop HDFS solving and how is that benefiting you?** Hadoop hdfs is solving big data by storing the data in distributed for in different machine. we are storing the hug amount of our enterprise which hold hug data related to various types of industrial information and data ### 14. Distributed storage with high throughput for storing large files **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Computer Software | Mid-Market (51-1000 emp.) **Reviewed Date:** May 13, 2023 **What do you like best about Hadoop HDFS?** It scales well with large datasets and provides high throughput for storing large files. It is open source, and the community is quite vibrant for helping in resolving issues. Plugins are available in multiple languages to use HDFS. **What do you dislike about Hadoop HDFS?** It's not fully HA even with 3-node HA deployment. If the two namenode servers go down, the HDFS cluster goes down. The throughput decreases if there are a lot of small files. And the data is not evenly stored across all the datanodes; not sure if it is related to our deployment configurations. **What problems is Hadoop HDFS solving and how is that benefiting you?** We use HDFS as a distributed storage for storing our internal files, which other processes can access from different nodes in the cluster. ### 15. Hadoop HDFS - Best for Big data Storage **Rating:** 4.5/5.0 stars **Reviewed by:** Swetha Y. | Senior Data Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** June 06, 2023 **What do you like best about Hadoop HDFS?** The best part about Hadoop HDFS is used to replicate data and it's architecture is easy to learn and implement.It helps in processing larger files in short period of time and it helps us to improve the performance. **What do you dislike about Hadoop HDFS?** Managing or developing a complex applications will be challenging.Main thing is it supports only bath processing not a real time data processing and not suitable for minimal data. **What problems is Hadoop HDFS solving and how is that benefiting you?** Large amount of data collection and storage and cheap to get this up and run.we us HDFs to store enterprise big data to develop an application which shows data flowing from source to sink. ### 16. Awesome Product **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Mid-Market (51-1000 emp.) **Reviewed Date:** June 14, 2023 **What do you like best about Hadoop HDFS?** HDFS ensures high fault tolerance through data replication across multiple nodes in the cluster, typically maintaining three copies of each data block. This replication strategy guarantees data availability in case of node failures, as HDFS automatically redirects requests to alternative replicas, thus preserving data integrity and reliability. **What do you dislike about Hadoop HDFS?** HDFS is primarily designed for batch processing and may not be the best choice for low-latency or real-time processing needs. Its data replication and block-based storage model introduce inherent delays in data access and processing, which diminish its suitability for real-time analytics or interactive queries. **What problems is Hadoop HDFS solving and how is that benefiting you?** Helping users and customers which belongs to our product with churn prediction using the data processed with Hadoop. Hadoop helps us in analysing data and processing huge amount of data in no time ### 17. Hadoop hdfs next level of computation **Rating:** 4.0/5.0 stars **Reviewed by:** Tanmay A. | Data Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** April 29, 2023 **What do you like best about Hadoop HDFS?** It completely change our processing speed as it is a distributed file system that help to do parallel processing so that solve our problem of processing of Tera bytes of data with horizontal scaling **What do you dislike about Hadoop HDFS?** It is very costly setup as it needs nods which is basically in it self cpu that need lots of Money to setup the cluster also small file problem means we can't store small file due to the meta information handling problem **What problems is Hadoop HDFS solving and how is that benefiting you?** It solving the problem for me by inhance my processing speed if I want to process Tera byte of data and take the useful information from that, that saves my time ### 18. Defacto standard for distributed File storage **Rating:** 5.0/5.0 stars **Reviewed by:** Sayan P. | Software Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** August 09, 2023 **What do you like best about Hadoop HDFS?** HDFS has been around for a while now. There are plethora of documentation and community support available. **What do you dislike about Hadoop HDFS?** Interacting with Kerberos authenticated HDFS can be esoteric and hard to understand initially. **What problems is Hadoop HDFS solving and how is that benefiting you?** We store all of Hive tables, arbitrary files for inter system communication on HDFS. We have started using Hudi on HDFS as well. ### 19. Distributed computing system **Rating:** 4.5/5.0 stars **Reviewed by:** Nishu G. | Test Engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** July 27, 2023 **What do you like best about Hadoop HDFS?** Fault tolerance facility,when data node failed it can use the other as replication factor is 3. **What do you dislike about Hadoop HDFS?** Support only batch processing engine,it cannot produce realtime output. **What problems is Hadoop HDFS solving and how is that benefiting you?** Distributed system process a large amount of data with high speed. ### 20. working and learning Hadoop makes things easier and much more effective to use. **Rating:** 4.5/5.0 stars **Reviewed by:** Shubham S. | Data Analyst, Small-Business (50 or fewer emp.) **Reviewed Date:** June 15, 2023 **What do you like best about Hadoop HDFS?** Hadoop is a widely used open-source framework for storing and processing extensive data sets because of its scalability, cost efficiency, Fault tollerence etc. **What do you dislike about Hadoop HDFS?** Hadoop has some disadvantages like its Complexity, Steep learning curve, high hardware requirement. **What problems is Hadoop HDFS solving and how is that benefiting you?** It helps me to process the vast amount of data stored in it from different significant data sources. ### 21. Hadoop_review **Rating:** 3.5/5.0 stars **Reviewed by:** Avinash K. | Data Scientist, Mid-Market (51-1000 emp.) **Reviewed Date:** June 21, 2023 **What do you like best about Hadoop HDFS?** Hadoop is very fast and flexible towards the data for implementing and improve the data quality **What do you dislike about Hadoop HDFS?** As per my experience Hadoop has no disadvantages as per my experience **What problems is Hadoop HDFS solving and how is that benefiting you?** It solves data downloading and data storage, it available the data in instant ### 22. Hadoop HDFS - One stop shop for your big data storage **Rating:** 5.0/5.0 stars **Reviewed by:** Aditya K. | Lead Software Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** August 05, 2022 **What do you like best about Hadoop HDFS?** Hadoop HDFS architecture is easy to learn and implement. HDFS has a bigger block size which increases the speed of data allocation (by reducing the latency). Hadoop HDFS does not only provide you the storage but also gives you an option to encrypt the data at rest as it supports KMS/KTS/RangerKMS encryption. **What do you dislike about Hadoop HDFS?** Hadoop HDFS is only for big files hence if you are storing a lot of small files or your ETL source is then HDFS performance gets impacted. A large number of small files increases the name node memory overhead and finally leads to slower throughput as it causes GC slowness. Hence my recommendation is to only use HDFS when you know you have to store or process large files ( >128MB) **What problems is Hadoop HDFS solving and how is that benefiting you?** Storing the data that comes from different sources like Abinitio, Informatica, Sqoop, databases and whatnot. Hadoop HDFS has connected with a lot of 3rd party software which helps in integrating HDFS to services that support JDBC and ODBC protocol. ### 23. Senior Software Engineer **Rating:** 4.0/5.0 stars **Reviewed by:** Abhinav Singh B. | Senior Software Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** June 07, 2023 **What do you like best about Hadoop HDFS?** Easier to handle the bulk of data, and it's innovative features. **What do you dislike about Hadoop HDFS?** Syntax differences as compared to trivial Java coding. **What problems is Hadoop HDFS solving and how is that benefiting you?** More convenient to use in massive databases than any NOSQL or SQL database. ### 24. I have worked on Hadoop, it is easy to work onit **Rating:** 5.0/5.0 stars **Reviewed by:** shubham k. | System Engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** June 09, 2023 **What do you like best about Hadoop HDFS?** Simplicity, re-use abilities, manintain, security, atomicity, integrity **What do you dislike about Hadoop HDFS?** Nothing. . . . .. . . . **What problems is Hadoop HDFS solving and how is that benefiting you?** Managing trafficking ### 25. Hadoop Hdfs **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Hospital & Health Care | Small-Business (50 or fewer emp.) **Reviewed Date:** June 14, 2023 **What do you like best about Hadoop HDFS?** HDFS is very user friendly it was very fast for data storing and data storage vary fast io over all my experience for hdfs is very good **What do you dislike about Hadoop HDFS?** Some time it will legging for some data process some external connections and all. **What problems is Hadoop HDFS solving and how is that benefiting you?** Data simplification ### 26. Hadoop Hdfs is used for parallel processing and distributed computing **Rating:** 5.0/5.0 stars **Reviewed by:** Kunal R. | System Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** August 10, 2022 **What do you like best about Hadoop HDFS?** Best part about Hadoop Hdfs is used to replicate data. It can be used to manage high data set(large data set). It is one of the main components of Apache Organization use it for high scalability. Large data from megapyte to pegabyte can be stored using this product and it also runs on low cost system. It helps tracking down the system faults and strengthen the system. It processes large amount of data quickly.It also helps in distributed storage **What do you dislike about Hadoop HDFS?** Well I am a current user of Hadoop Hdfs and till now I haven't found any cons about this product. **What problems is Hadoop HDFS solving and how is that benefiting you?** Using Hadoop Hdfs we can process large volume data and it can be done quickly.It has 2nodes name node and data mode.Name node maintain data nodes and works as Head node/master node.Data node stores actual data and instruct what needs to be done about the data.Heavy data can be stored using Hadoop Hdfs.All nodes are organised is a same rack.Large data is broken into small data and based on need it is sent to data nodes.Great product for scalability.Used in replication.Helps track down faults. ### 27. Hadoop distributed file system **Rating:** 5.0/5.0 stars **Reviewed by:** Bidisha P. | Senior Speclialist (Vendor Master Data), Enterprise (> 1000 emp.) **Reviewed Date:** August 05, 2022 **What do you like best about Hadoop HDFS?** Hdfs is highly scalable as it supports horizontal scaling. HDFS also boasts encryption at rest which is helpful as our data is secured so we do not have to worry. It also has some integrations to mask the PII data to hide sensitive information **What do you dislike about Hadoop HDFS?** Hdfs gets slow at times and the stack support folks takes a lot of time to find the root cause. Hadoop slowness also affects the throughput and ultimately affects business as reports get delayed **What problems is Hadoop HDFS solving and how is that benefiting you?** Storage at large scale Hosting multiple solutions Encryption of data at rest Scalability Integration with ETL tools as well as Java supported applications Trash feature helps to clear historical data periodically ### 28. Data Engineer using Hadoop **Rating:** 5.0/5.0 stars **Reviewed by:** Jay C. | Associate Software Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** September 23, 2022 **What do you like best about Hadoop HDFS?** Everything goes smooth either while copying files from Multilocation **What do you dislike about Hadoop HDFS?** It has dependencies on Linux, which is why we need to learn Linux code while working on edge node **What problems is Hadoop HDFS solving and how is that benefiting you?** Cross platform Independence and open source has helped us to work independently and adopt any new technology ### 29. Review on Hadoop HDFS **Rating:** 4.0/5.0 stars **Reviewed by:** Arijit C. | Data Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** September 20, 2022 **What do you like best about Hadoop HDFS?** It helps Big Data processing be easier. Earlier, processing large files would take a lot of time to process, but with HDFS, we gained a lot of performance optimization. **What do you dislike about Hadoop HDFS?** There is a lot of I/O operations while processing Big Data. In this aspect, Spark is performing much better due to its in memory calculations. **What problems is Hadoop HDFS solving and how is that benefiting you?** HDFS helps in solving big data problems in life. It helps to process TBs of data in a few hours, which was impossible to do with the traditional system. ### 30. In Hadoop Data lake we were using autosys to automate Hadoop jobs. **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Broadcast Media | Enterprise (> 1000 emp.) **Reviewed Date:** June 30, 2022 **What do you like best about Hadoop HDFS?** It is really easy to run shell-based as well as code-based applications through autosys. Also, you can pass output from one step to other steps in autosys. **What do you dislike about Hadoop HDFS?** overall as a scheduler I didn't find anything which is not supported in autosys. **Recommendations to others considering Hadoop HDFS:** If you have a very large amount of data and data is unstructured in that case you can use Hadoop. You can create a data lake concept very easily from Hadoop. **What problems is Hadoop HDFS solving and how is that benefiting you?** We were receiving two types of data in Hadoop data lake. One is from our internal system and the other is from vendors. So we were using autosys to process vendor's data. The reason was we could not give outsiders access to our environment so we installed autosys agent on edge nodes and they were able to automate jobs from there. ### 31. Hadoop-Best Distributed System **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Computer Software | Enterprise (> 1000 emp.) **Reviewed Date:** September 03, 2022 **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. **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. **What problems is Hadoop HDFS solving and how is that benefiting you?** Hadoop HDFS is solving the problem of the distributed file system. It provides functionality to store data/files on different clusters or nodes and allows to access them at marginal cost with high accuracy and low fault. ### 32. How hadoop is so powerful to use for data Analysis **Rating:** 4.5/5.0 stars **Reviewed by:** Arpan s. | System Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** January 07, 2022 **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. **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. **What problems is Hadoop HDFS solving and how is that benefiting you?** We have use the HDFS for mantaining the larger amount of data for the analysis purposes. With the help of POWER BI we use the data for analysis and take better business decisions for the growth of any product based company. ### 33. Hadoop HDFS Review **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Enterprise (> 1000 emp.) **Reviewed Date:** July 26, 2022 **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 minimising the latency for data processing **What do you dislike about Hadoop HDFS?** No concept of data replication across multiple availablity zones like provided by public cloud and Fix cost even if minimum volume is consumed on hdfs. **What problems is Hadoop HDFS solving and how is that benefiting you?** Data processing in parallel manner to handle large amount of data to generate our financial reports while meeting the ETAs ### 34. Best distributed file system for Big Data storage and analysis **Rating:** 5.0/5.0 stars **Reviewed by:** Kubendra Reddy M. | Data Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** March 04, 2022 **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. **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. **Recommendations to others considering Hadoop HDFS:** Strongly recommend if you are storing and processing big data. **What problems is Hadoop HDFS solving and how is that benefiting you?** We are storing our data in hdfs and used to process the data with hive and spark.Mainly we used this for batch data processing. ### 35. Recommend Hadoop **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Enterprise (> 1000 emp.) **Reviewed Date:** September 08, 2022 **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 **What do you dislike about Hadoop HDFS?** Hadoop only supports batch processing and also because of distributed algo latency increases **What problems is Hadoop HDFS solving and how is that benefiting you?** Helps in processing very large data and it is open source ### 36. HDFS review **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Automotive | Enterprise (> 1000 emp.) **Reviewed Date:** August 24, 2022 **What do you like best about Hadoop HDFS?** Distributed storage and high availability of data.Multiple processing engines supported like MR Tez and spark **What do you dislike about Hadoop HDFS?** Slow adhoc queries for analytics. No concept of faster reads like AWS athena . **What problems is Hadoop HDFS solving and how is that benefiting you?** Batch reporting jobs on sales data for creating tableau reports ### 37. How Hadoop HDFS is best file system for Big Data applications. **Rating:** 5.0/5.0 stars **Reviewed by:** Chintan M. | Assistant System Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** September 28, 2021 **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. **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. **Recommendations to others considering Hadoop HDFS:** I strongly recommend using Hadoop HDFS as a storage system in Big Data applications. **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. ### 38. Efficient tool for large amount of data processing **Rating:** 4.5/5.0 stars **Reviewed by:** Lee T. | Market Strategy Planning Manager, Enterprise (> 1000 emp.) **Reviewed Date:** September 17, 2021 **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. **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. **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. **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. ### 39. Offline batch process for high volume and multi format of data **Rating:** 4.0/5.0 stars **Reviewed by:** Pawan K. | Bigdata Platform Architect at HCL Technologies Limited, Enterprise (> 1000 emp.) **Reviewed Date:** January 20, 2022 **What do you like best about Hadoop HDFS?** Distributed file system process and multi-tenant environments **What do you dislike about Hadoop HDFS?** More admin works required for cluster management **Recommendations to others considering Hadoop HDFS:** If you want to analyze and enhance the current business pls, start to use a data analytics project with Hadoop service **What problems is Hadoop HDFS solving and how is that benefiting you?** Data analytics on high volume and multi-variety of data ### 40. Most reliable filesystem **Rating:** 4.5/5.0 stars **Reviewed by:** Ankit K. | System QA Sr Analyst, Enterprise (> 1000 emp.) **Reviewed Date:** December 14, 2021 **What do you like best about Hadoop HDFS?** Unique design thatprovides storage for extremely large files with streaming dara access pattern and run on commodity hardware. **What do you dislike about Hadoop HDFS?** Security concern , managing a complex applications can be challenging. Vulnerable by nature, not fit for small data. **What problems is Hadoop HDFS solving and how is that benefiting you?** When dealings with extremely large data. & Wanted to write once & read many times. Inexpensive hardware. Large computation. ### 41. Hadoop HDFS-Best Storage for Distributed Computing **Rating:** 5.0/5.0 stars **Reviewed by:** Deepika T. | Data Engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** August 28, 2021 **What do you like best about Hadoop HDFS?** All the things are best about HDFS. We can store data in different formats, be it parquet, text, ORC anything. It supports parallel computing, so it is easy to store vast amounts of data in partitions in blocks. **What do you dislike about Hadoop HDFS?** Sometimes it is difficult for a new learner to access the HDFS using the command line. It is a bit difficult to learn all the queries. **What problems is Hadoop HDFS solving and how is that benefiting you?** Our company basically works on Big Data, so storing big data is not easy. So to store big data, we use HDFS as we can store data in blocks and can be easily accessible. ### 42. Best tool to store big data **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Financial Services | Small-Business (50 or fewer emp.) **Reviewed Date:** October 08, 2021 **What do you like best about Hadoop HDFS?** The best about HDFS is that we can store different types of data at a single point in time as well as in other formats also. It also supports parallel computing, due to which it becomes easy to store extensive data. **What do you dislike about Hadoop HDFS?** The only thing that I dislike is that it becomes difficult for beginners to understand to access the command line. It is a bit difficult to learn all. **What problems is Hadoop HDFS solving and how is that benefiting you?** The problem solved by the HDFS is the problem of storing big data, as storing big data is not an easy task for the company as in HDFS, data can be stored in blocks and is easy to access. ### 43. If you are from Bigdata or Analytics background, you need to use HDFS. My experience is very good. **Rating:** 5.0/5.0 stars **Reviewed by:** AAKASH C. | Software Analyst, Enterprise (> 1000 emp.) **Reviewed Date:** April 29, 2021 **What do you like best about Hadoop HDFS?** Distributed storage and resilience of the data. Handling multiple file formats like parquet and avro and the connectivity with the other systems. Its integration with the hadoop map reduce and the processing frameworks like spark. Syntax similar to normal file system if you have knowledge about unix or other file system. Easily Scalable. Easy to learn and configure. Can be used with traditional mapreduce as well as latest frameworks like Spark, Storm and Scalding. Can be setup on a virtual private cloud instance They are also very cost effective. **What do you dislike about Hadoop HDFS?** Setup and the syntax are little bit slow to learn if you are not from familiar background. There are other better options like S3 and others for storage if you are using cloud like AWS. Issues with small files. Support for batch processing. No real time data processing. Architecture is little complex i.e. all the terms like name node, data node difficult to grasp in first time. Need to have knowledge of different components if you want to utilize the full power of hdfs. Sometimes there is data loss too if you dont configure the rack and replication factor properly. Documentation stuff is little difficult to understand for the first time user. **What problems is Hadoop HDFS solving and how is that benefiting you?** My main problem that hdfs solved is of storing the TBs of banking data and allowing it to process smoothly using Spark. Problems of storage of large files on a single system. Also the problems when writing the data using spark using the different compression techniques like gzip and snappy. Easy to access the data from hdfs while processing. Storage of files with multiple file formats is a benefit. Also the main benefit is partitioning i.e. the data is stored in the partitions. Can be setup on a single standalone machine too. Free and open source Performant and cheap and easy to use. ### 44. Durable and consistent storage **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Enterprise (> 1000 emp.) **Reviewed Date:** December 24, 2021 **What do you like best about Hadoop HDFS?** It is very easy to setup It is really useful strong consistency use cases It can scale seamlessly **What do you dislike about Hadoop HDFS?** Requires too much of maintenance downtime during compaction when used with hbase Lot of parameters to tune and look into **What problems is Hadoop HDFS solving and how is that benefiting you?** we are using it for HBase as a datastore and i had setup ambari and used to manage it through ambari. Sometime the cluster is unavailable due to compaction ### 45. Hadoop HDFS Review **Rating:** 4.0/5.0 stars **Reviewed by:** Okan Y. | Student, Mid-Market (51-1000 emp.) **Reviewed Date:** January 27, 2021 ### 46. Hdfs is great for big data processing **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Mid-Market (51-1000 emp.) **Reviewed Date:** October 15, 2021 **What do you like best about Hadoop HDFS?** Supports large files, scalable and uses comodity hardware **What do you dislike about Hadoop HDFS?** Consistency and acid properties are not working **Recommendations to others considering Hadoop HDFS:** Scalable and large volume processing **What problems is Hadoop HDFS solving and how is that benefiting you?** Big data processing jobs. Batch and streaming processing ### 47. It's not just a data lake, it's an gain data ocean **Rating:** 5.0/5.0 stars **Reviewed by:** Lakshmi Narayana J. | Senior Hadoop Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** January 05, 2021 **What do you like best about Hadoop HDFS?** Date storage for better data warehousing **What do you dislike about Hadoop HDFS?** There are no features that are down side **Recommendations to others considering Hadoop HDFS:** It is the first and always recommend service to store historical data **What problems is Hadoop HDFS solving and how is that benefiting you?** To leverage vast storage and to achieve easier and efficient way of storing a retrieving data ### 48. HDFS... Cluster is awesome **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Enterprise (> 1000 emp.) **Reviewed Date:** May 05, 2021 **What do you like best about Hadoop HDFS?** Fault Tolerance, Scalability, Availability **What do you dislike about Hadoop HDFS?** Command Based Interface, Linux Architecture **What problems is Hadoop HDFS solving and how is that benefiting you?** Importing Exporting Large Amount of Data. It is very fast ### 49. High scalability with HDFS **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Internet | Enterprise (> 1000 emp.) **Reviewed Date:** April 25, 2020 **What do you like best about Hadoop HDFS?** Open source, easy scalability and simplicity for warehouse usages **What do you dislike about Hadoop HDFS?** Its not for real time applications and not transactional system support **Recommendations to others considering Hadoop HDFS:** Hadoop has power of parallelism but needs better real-time transactional support **What problems is Hadoop HDFS solving and how is that benefiting you?** I am using HDFS with Spark/Presto for analytics use cases only ### 50. Hadoop HDFS Review **Rating:** 4.5/5.0 stars **Reviewed by:** Sejal W. | Software Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** May 24, 2019 **What do you like best about Hadoop HDFS?** The main key point about Hadoop is that allows you to efficiently store big data as well as process big data. It stores data using HDFS and processes it using MapReduce. This serves the main need of storing and processing the tons of data we are generating everyday. The second best part is that it is a free software for anyone to access! **What do you dislike about Hadoop HDFS?** Every user should know that using hadoop for small data is not a good idea, it will only make the easy task difficult. It requires a lot of space to be installed on your laptop. It is a vast platform to learn quickly. **Recommendations to others considering Hadoop HDFS:** Definitely a go to App for big data analysis. Experience with Hadoop can take you one step further if you are in the field of big data. **What problems is Hadoop HDFS solving and how is that benefiting you?** Being in the field of data analytics, I use Hadoop to store the large data generated by my company. This data is further used for processing. ## 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?section=pricing&secure%5Bexpires_at%5D=2026-06-09+09%3A23%3A36+-0500&secure%5Bsession_id%5D=935ee1b9-c53a-4c3c-83c1-0bc12316c6ab&secure%5Btoken%5D=446a98959050d9eaf9d84d26d71cc288a4a73ae5ca17f8db495ba3d3ae6a5a3f&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 - [Google Cloud BigQuery](https://www.g2.com/products/google-cloud-bigquery/reviews) - 4.5/5.0 (1,148 reviews) - [Databricks](https://www.g2.com/products/databricks/reviews) - 4.6/5.0 (781 reviews) - [Cloudera Data Platform](https://www.g2.com/products/cloudera-cloudera-data-platform/reviews) - 4.1/5.0 (131 reviews)