Hadoop Distributions Reviews and Ratings

MapR is built for performance and scale. Among other things, the file system is not HDFS and hence removes all the limitation of HFFS. It is a full read/write files system, which means you can use industry protocols like NFS to ingest data. The default file size is 8kb, which means you can do small writes instead of the 64MB/128MB that is required for HDFS.

We are using this product to store the customers history data in cloud. It is very fast, reliable cloud service where we can store data in hierarchical data.

it is a fast and reliable solution that combines the great Data utility, storage and data analysis features.It supports multi-dimensional comparisons as well as high-performance analysis and querying.

GCP is very powerful distributed platform to share the files or store the file. We can easily store and share the file to other with privacy which one has access of the bucket. It is much easier while cluster job execution.

Incredible cloud data processing solution, works with the best hadoop suite tools. With this solution we can perform large scale processing in a short time because it is possible to create processing clusters.

Apache product is very flexible and easy to manage our integration with other downstream systems. All the web components and logging is easy to trace.

Very good and it helpful great product The data lake analytics tool is good, and provides loads of compute power to speed up processing time

I've used this product for Big Data Testing Purpose and I've done lots of R&D on it. It is very smooth and easy to understand the environment. One thing you need Basic of Unix/Linux command is necessary to use this

Oracle Big Data SQL is very useful in analysing datas, Also extracting datas from databases are also easy. It enables us to analyse datas across Apache Hadoop, Apache Kafka, NoSQL, object stores and Oracle Database. And gearing the skills, security policies and applications with extreme performance.

Oracle stepped up and provided the resources necessary to make the project a success.

Microsoft is aggressively adding Azure capabilities to its cloud solutions like Office 365 email, OneDrive for Enterprise but Microsoft cannot use EDM for structured data. This is critical for us.

Overall Experience: Oracle Big Data is a most helpful software when one is working with a large amount of data. Oracle Big Data acquires data from a large variety of sources. The data acquired is analyzed at ridiculous speeds and scales. There is no worry about spyware or virus downloads as Oracle Big Data comes with a top grade security which safe guards the data collected.

well solution for hadoop ECO system, and it's easy to deployment and management. Software upgrade should be faster.

1 of a kind or not as good as this competitor. I Hope xx develops a competition with Cloudera

AWS has worked as expected

The automatic installation, deployment and operation and maintenance management of the star ring products are very convenient, and the SQL support is also very high. The cost of migrating the original system applications to the platform is low, and the operation performance is better. User manual should be updated in time.

Because of a pre-existing relationship the implementation was successful. More documentation and benchmarking of multiple cluster services (Spark, Zappelin and Ambari) and multiple data formats (ORC, Parquet ...) would help in determining what is best for which analytic use cases and business situations.

Hadoop is a solution to solve the problem called 'big data'. Hadoop is a very big Dataware house that can take data from anywhere at any time. It stores and processes the data. Hadoop is today's choice because of its scalability, high degree of dependability and support for wide range of workload types.

Bigdata is used for high level data processing of large databases. Basically this is used for data mining by maitaining the performance