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Product and Topic Expert
Product and Topic Expert

SAP HANA Vora provides an in-memory processing engine which can scale up to thousands of nodes, both on premise and in cloud. Vora fits into the Hadoop Ecosystem and extends the Spark execution framework.

Following image shows you where Hadoop fits in the Hadoop ecosystem:

Recently, Vora 1.2 has been released with the following new features:

  • Support for MapR Hadoop distribution
  • Vora modeler – for building data models on top including OLAP
  • Added features to Hierarchies
  • Dlog, Discovery services using Consul tool
  • Enhanced performance through partitioning and co-located joins

The focus of this blog is to introduce you to the Vora Data Modeling tool.

For more information on other features released with 1.2 please refer to:

and for more information on the concepts such as DLOG, Discovery Service, Vora configuration and installation please refer to:

Vora 1.2 installation Cheat sheet: Concepts, Requirements and Installation

Vora 1.2 Modeling Tool:

In order to communicate with Vora engine, you could use Apache Zeppelin or Jupyter Notebook(, mostly for coding.

We also designed the Vora modeling tool (modeler) to facilitate the development across structured, unstructured and semi-structured data and has been released as a beta version with Vora 1.2 .With Vora modeler you have access to SQL editor and also the Modeler perspective which give you the option to code or drag and drop the artifacts to develop your data view.

By installing the Vora Tools as part of the Vora 1.2 installation, you will have access to Vora modeler through your browser and via the port 9225:


Here is how your modeling home page should look like. This page will give you access to the main perspectives, connection feature and help.

Vora Modeling has three main perspectives:

  • Data Browser
  • SQL Editor
  • Modeler

Data Browser allows you to view the available tables, views, dimensions and cubes in Vora engine. It also allows you to have a preview of the data, download the data as a CSV file, filter the columns and refresh them.

Here is a view of your Data Browser:

SQL Editor perspective allows you to run the queries on Vora engine using Vora SQL, it also shows you the compilation warnings, errors and outputs and the result of the query when you run the select.

The Modeler perspective could be used to create SQL views, Dimensions or Cubes. You could also use the subselect artifact to create the nested queries. Below you could see a view of the Modeler:

For more information on how to use the Vora modeler and create data analysis scenarios (using joins, unions, etc) refer to Vora Developer's Guide, Chapter 11.

To summarize, we should mention that the support for the following features are available in Vora 1.2:

  • Dimensions and Cubes
  • Annotations
  • Joins
  • Simple and multiple joins
  • Auto propose the join conditions
  • Define the join condition using an editor
  • SQL Editor supporting VORA SQL
  • Modeling perspective
  • Subselect
  • Unions
  • Union has been visualized with the notion of resultset, provide better management of groupby, orderby etc at different levels
  • Regenerate the views as Spark SQL
  • Exporting the tables as CSV