What is the difference between the Smart Data Access of SAP HANA and SAP HANA Vora

Question

Which one is the better way to analyse  hot (SAP HANA) and cold(Hadoop) data in one analysis, written by SAP HANA tools? Needed some explanation.

Answer 1

SAP HANA and Hadoop are two different things. SAP HANA is an ANSI SQL database.  It maintains ACID constraints, and therefore is good for transactional & analytical applications. It is high performing database which is good for transactional applications. You can also go ahead and execute complex queries over this high performing database.

Hadoop is a framework that allows you to store large datasets in a distributed environment, so that, you can process it parallely. The power of Hadoop lies in storing data that can be of different varieties, i.e. structured, semi-structured & un-structured data. But Hadoop is not suited for transactional applications.

Talking about SAP HANA VORA, it is in-memory query engine which extends Apache Spark execution framework to provide interactive analytics on Hadoop. It provides in-memory processing on top of Hadoop and enterprise functionality to simplify the IT landscape for organisations.

To summarize I would say, HANA is an in-memory database which focuses on performance, while Hadoop’s power lies in reducing the storage cost. SAP HANA can be used for transactional purposes & Hadoop can used for storing unstructured data in an efficient manner.

Answer 2

Hadoop: Used to store Big Data in a distributed manner for processing in multiple systems and therefore provides a fault-tolerant way of storage and processing by replication.
Spark: Provides In-Memory computations and real-time streaming framework.
SAP HANA VORA: Best of both worlds in an easy to use bundle. It is an in-memory query engine that plugs into the Apache Spark execution framework to provide enriched interactive analytics on Hadoop. SAP HANA Vora builds structured data hierarchies for the Hadoop data and integrates it with data from HANA to enable OLAP-style in-memory analysis on the combined data through an Apache Spark structured query language (SQL) interface. HANA Vora uses HANA’s in-memory database, which can perform real-time processing, and then adds an analytic layer to handle Hadoop data. This allows Vora to take the huge amounts of data stored in Hadoop and integrate it with data from enterprise systems so that developers and data analysts have instant access to the aggregated data and can make contextually-aware decisions.

Hope this helps.