Compatibility between the Big Data vendors
What the Big Data vendors have to offer?
Finally that the Big Data wars have pretty much ended, we have got Cloudera , MapR and Hortonworks as the major Big Data vendors. There are also other pure vendors that focus on one or two Big Data softwares (like DataStax on Apache Cassandra), but the above mentioned Cloudera, MapR and Hortonworks vendors provide a complete suite of softwares covering storage, processing, security, easy installation etc. These vendors solve some of the problems like
Integrating the different softwares from Apache. Not every Big Data software from Apache is compatible with other. These vendors make sure that the different softwares from Apache play nice with each other.
Installation and fine tuning of the Big Data softwares is not easy. It’s no more download and click. These vendors make the installation process easier and automate as much as possible.
Although the software from Apache is free to use. Apache Software Foundation doesn’t provide any commercial support. Companies like Cloudera, MapR and Hortonworks fill the gap as long as the software from these vendors is being used.
Compatibility between the different Big Data vendors?
It’s all fine and dandy till now. One of the purpose of using Open Source Software is to avoid vendor lock-in. But, the different Big Data vendors deliberately or not cause customers to lock into their software. Here we will look into it.
The suite from the different vendors is actually a combination of different softwares. For example Cloudera CDH is a combination of Hadoop, Hive, Pig, Sqoop, Oozie and a variety of different Big Data softwares. These and others are the common set of softwares in the different distributions. But, on top of them the vendors promote unique softwares which makes them incompatible with others.
For example, Cloudera pushes Impala for Big Data Analytics, but Hortonworks had been pushing Hive for the same. Cloudera includes Impala in their distribution, while Hortonworks doesn’t include in its distribution. Impala and Hive are similar to an extent that they provide an SQL like interface for the user.
