Hadoop HDFS Reviews & Product Details

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

It is very easy to setup

It is really useful strong consistency use cases

It can scale seamlessly Review collected by and hosted on G2.com.

Requires too much of maintenance

downtime during compaction when used with hbase

Lot of parameters to tune and look into Review collected by and hosted on G2.com.

Supports large files, scalable and uses commodity hardware Review collected by and hosted on G2.com.

Consistency and acid properties are not working Review collected by and hosted on G2.com.

Date storage for better data warehousing Review collected by and hosted on G2.com.

There are no features that are down side Review collected by and hosted on G2.com.

Fault Tolerance, Scalability, Availability Review collected by and hosted on G2.com.

Command Based Interface, Linux Architecture Review collected by and hosted on G2.com.

Open source, easy scalability and simplicity for warehouse usages Review collected by and hosted on G2.com.

Its not for real time applications and not transactional system support Review collected by and hosted on G2.com.

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! Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.