Hadoop HDFS Reviews & Product Details

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

Hadoop's storing of large amount of data into a clusters that makes data as fault tolerant, secure and faster processing and scalability Review collected by and hosted on G2.com.

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 Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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 Review collected by and hosted on G2.com.

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 Review collected by and hosted on G2.com.