As the world of Big Data, Machine Learning and Artificial Intelligence is taking off, there is an overlap of roles and responsibilities of various designations in different companies. You have various flavours of the same job description, called by different names. There are business analysts, data analysts, data scientists, data engineers, machine learning engineers, software engineers, and management consultants all vying for parts of the new pie. Even as enterprises are cr

We have looked at HBase Fundamentals and HBase Architecture in the last two weeks. Today I will look at a few best practices and guidelines that will help in designing the schemas suitably for HBase. The design of schemas, regions, parameters, region servers and their sizes, the caching strategies are all covered here. A warning that this assumes you have HBase working knowledge and are dealing with improving its performance. Your design considerations are very specific to ea

We looked at the basics of HBase in the previous article, last week. Today we will understand the Architecture of HBase. We all agree that software architecture is a sort of a plan of a system the helps in understanding the initial decisions taken, the trade-offs made and gives an idea about how the systems were intended to be used and thus equips the user of the software to use it appropriately. It makes it easier to understand the whole system and makes the decision-making

HBase is a NoSQL DB that uses some capabilities of the Hadoop ecosystem to provide its features. NoSQL DBs (a.k.a Not Only SQL) are non-tabular stores that store data very differently from Relational Databases. The main types are document DBs, key-value stores, columnar DBs and Graph DBs. They provide flexible schemas and high levels of scalability. In this article, I introduce HBase and its associated concepts - its basic features, the data model and the various ways to acce