What’s New in SAP HANA Cloud in September 2022
Summer is slowly coming to an end, at least for the colleagues located in the northern hemisphere. And with the end of the summer, we are also approaching yet another end of a quarter. With this blogpost, I want to provide you with a summary of the exciting innovations that have been introduced to SAP HANA Cloud in Q3 2022. In case you want to take a quick glimpse at some of features introduced, take a look at my personal QRC3 2022 highlight via our teaser.
To get a detailed overview of individual functionalities and changes, including demos and a Q&A, don’t miss out and register now for our release webinar hosted by the SAP HANA Cloud product management team.
But for now, let’s look at the main highlights of the recent SAP HANA Cloud release:
Innovations in
SAP HANA Cloud, data lake
Our petabyte scale data lake is an integral part of SAP HANA Cloud. It allows users to store and manage all their data in a single solution. No matter, if you are looking for in-memory storage, disc capacity for warm data, or petabyte scale storage options, SAP HANA Cloud offers all in one box.
Always striving for improvements to our product, there is one especially notable innovation in QRC3 2022 for the SAP HANA Cloud, data lake.
Store relational engine data in SAP HANA Cloud, data lake Files storage
With the QRC3 2022 of SAP HANA Cloud, it is now possible to store SAP HANA Cloud, data lake relational engine data inside of the SAP HANA Cloud, data lake file storage.
This reduces data storage costs significantly. Moreover, scalability and throughput are improved. There is no need to over-provision storage any longer, to improve performance.
Last but not least, compute and storage resources are separated more clearly.
If you are curious to learn more about the change introduced, take a look at Jason Hinsperger‘s blog post.
These newly introduced functionalities offer a higher degree of control when upgrading and provisioning SAP HANA Cloud, SAP HANA database instances. Users are no longer forced to choose the latest version when upgrading or provisioning. This way instances and landscapes can be kept aligned on different QRCs more easily.
Built-in Betweenness Centrality algorithm & page rank algorithm
By the end of Q3 2022, two additional built-in graph processing algorithms are supported within the SAP HANA Cloud, SAP HANA database: The betweenness centrality algorithm and the page rank algorithm.
The first one helps to detect the most influential node for information flow in graph networks. It provides a measure of centrality in a graphs based on shortest paths and supports wide application in network theory.
betweenness centrality alogrithm – example
The second algorithm helps to detect the most important node in a graph network. It provides a measure of number of incoming relationships and the most important source nodes.
page rank algorithm – example
Both built-in algorithms are exposed through stored procedures written in GraphScript in SAP HANA Cloud, SAP HANA database. Moreover, both can easily be applied and displayed via the SAP HANA database explorer. You can integrate the algorithms into SQL statements, embed them into other SQL procedures and copy as well as adjust them to your specific business needs. Both therefore, enable simpler and faster development of applications that use graph processing.
The built-in graph processing capabilities, in general, allow low-code and no-code principles to be applied which reduce the programming and testing effort, and eliminate the need for specialized programming skills for graph processing, ultimately resulting in lower TCO.
Support for JSON object expression and JSON string in SQL statements
Since the latest release of SAP HANA Cloud, the SAP HANA database document store now supports object expressions, where string literals have single quotes in SQL statements and JSON strings, where string literals have double quotes in SQL statements.
With the broadened support, database developers can choose to use the well-known object expression in SQL or JSON strings, which are popular in various client programming languages.
Greedy pruning to speed up query processing in calculation views
We are once again enhancing the performance of statements, while also reducing the resource consumption during join execution: The greedy pruning option ensures that joins are only executed if they are required to retrieve requested columns. It is independent of the join type or the cardinality setting. You can activate greedy pruning for the left, the right, or both sides of a join.
In case you want to learn about all other innovations introduced in the area of Calculation View Modeling in SAP HANA Cloud, take