Big Data. Big Decisions
InformationWeek
Special Coverage Series


SAP Sweetens Hana Deal With Free Sybase Database



(Page 2 of 2)

Perhaps customer ambitions (and costs) will change over the long term, but for now, a dual-database strategy is a given. And for all those non-critical applications, replacing Oracle or IBM DB2 with ASE as the application database would be less expensive than moving onto Hana.

Companies need databases for reasons other than running SAP's software, so it's an open question whether they'll take to ASE. It's a venerable, highly scalable database that's widely used in the banking industry, but it has a tiny market share compared to Oracle, IBM DB2 and Microsoft SQL Server. What's more, it was certified to run Business Suite only last year, so SAP customers aren't exactly familiar with the product. As a SQL-based relational database, it has much in common with the other products, but database administrators and IT shops are known to be resistant to change. On the other hand, free is a powerful inducement to at least consider a change.

More Insights

Webcasts

More >>

White Papers

More >>

Reports

More >>

The ASE deal is significant, but because it's an OLTP database, the advantage to customers only goes so far. On the analytic (OLAP) side, SAP chairman Hasso Plattner acknowledged last week that customers will still need data warehouses (running on still other databases) to bring disparate data sources together and to transform and cleanse data.

It was not startling to hear that SAP customers will still need their data warehouses; it was always pretty obvious that deep historical data and non-SAP data weren't likely to be addressed by Hana. With SAP's low-latency data-integration technologies there is an opportunity to bring third-party data into real-time analytics scenarios on Hana, SAP execs told InformationWeek last week. But data warehousing is another spot where Hana won't address all needs (and there's no talk of bundling SAP's Sybase IQ analytic database to fill that void).

[ Want more on SAP's big move? Read SAP Moves Core Applications To Hana In-Memory Platform. ]

One more caveat regarding analytics: "dramatic simplification" might not involve disruption of the SAP landscape, but if you're going to eliminate aggregates, cubes and other performance aids that are no longer necessary with powerful in-memory technology, be prepared to rework the database model as well as dependent analytics and business intelligence reports. Dependencies on database artifacts don't magically disappear when you swap in Hana.

Add it all up and Oracle actually has a stronger "without disruption" story with Exalytics than does SAP with Hana -- assuming you're committed to using Oracle's bundle of hardware, database and analytical software, meaning Oracle Exadata and Oracle Business Intelligence Enterprise Edition. Without doing any modifications, you can run Oracle apps and middleware and even SAP apps on Exadata and gain incremental, cache-based analytic acceleration with Exalytics. With SAP you'll need two different databases -- at least for now -- because not all Business Suite apps run on Hana.

SAP's in-memory platform, meanwhile, gives you a better shot at delivering game-changing performance improvements and developing never-before-possible applications. You also get a shot at consolidating and simplifying infrastructure and eliminating data redundancies (likes aggregates and materialized views) because Hana can run both transactions and analytics.

Customers choosing Hana will need ASE or another database alongside it over the short term, and they may continue to use it over the long term where in-memory performance isn't needed. They'll also continue to need conventional data warehouses. Nonetheless, Business Suite on Hana beta customers like John Deere anticipate transformational performance on key, mission-critical business processes, and that has been the promise all along. SAP customers will undoubtedly want to see more customer examples before they're convinced that they, too, will be able to realize big advantages by reinventing key applications on Hana.

« Previous Page | 1 2  


Related Reading




Currently we allow the following HTML tags in comments:

Single tags

These tags can be used alone and don't need an ending tag.

<br> Defines a single line break

<hr> Defines a horizontal line

Matching tags

These require an ending tag - e.g. <i>italic text</i>

<a> Defines an anchor

<b> Defines bold text

<big> Defines big text

<blockquote> Defines a long quotation

<caption> Defines a table caption

<cite> Defines a citation

<code> Defines computer code text

<em> Defines emphasized text

<fieldset> Defines a border around elements in a form

<h1> This is heading 1

<h2> This is heading 2

<h3> This is heading 3

<h4> This is heading 4

<h5> This is heading 5

<h6> This is heading 6

<i> Defines italic text

<p> Defines a paragraph

<pre> Defines preformatted text

<q> Defines a short quotation

<samp> Defines sample computer code text

<small> Defines small text

<span> Defines a section in a document

<s> Defines strikethrough text

<strike> Defines strikethrough text

<strong> Defines strong text

<sub> Defines subscripted text

<sup> Defines superscripted text

<u> Defines underlined text

BYTE encourages readers to engage in spirited, healthy debate, including taking us to task. However, BYTE moderates all comments posted to our site, and reserves the right to modify or remove any content that it determines to be derogatory, offensive, inflammatory, vulgar, irrelevant/off-topic, racist or obvious marketing/SPAM. BYTE further reserves the right to disable the profile of any commenter participating in said activities.

Disqus Tips To upload an avatar photo, first complete your Disqus profile. | View the list of supported HTML tags you can use to style comments. | Please read our commenting policy.

Follow InformationWeek

By The Numbers

What Are Your Primary Concerns About Using Big Data Software?

Base: 417 respondents at organizations using or planning to deploy data analytics, BI or statistical analysis software
Data: InformationWeek 2013 Analytics, Business Intelligence and Information Management Survey of 541 business technology professionals, October 2012

What Do You Think?

What's your attitude about SQL analysis on top of Hadoop?
We want fast, standard SQL analysis capabilities on Hadoop ASAP
Hadoop is for unstructured data; SQL is for relational databases
We'll give SQL on Hadoop a try, but relational DBs will remain the mainstay
Given strong SQL support on Hadoop, we'd nix the data warehouse
We're not interested in Hadoop
No opinion



Related Content

From Our Sponsor

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Business leaders often need a visual snapshot of data to quickly grasp and use it. This paper identifies five challenges in presenting data and how visual analytics can resolve them. Solutions are suggested to overcome the challenges of: speed, data clarity, data quality, displaying meaningful results, and dealing with outliers.

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Today's competitive advantage requires a deeper understanding of your business, your market and your customers. As an IT executive, you can drive that knowledge transformation. In this white paper, learn how to make decisions as a strategic business leader and three steps to begin an analytics initiative within your enterprise.

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

High-performance data visualization turns sophisticated analyses into meaningful graphics, leading to faster and smarter decision making. In this white paper, learn how visual analytics can transform big data, with additional features such as real-time functionality, mobile compatibility, robust applications for technical groups and accessibility for nontechnical users.

Big Data: Lessons from the Leaders

Big Data: Lessons from the Leaders

Financial performance, competitive advantage, operational efficiency, strategic decision making - every business goal can extract value from big data, and the time for doubt or inaction has long passed. In this Economist Intelligence Unit report, in-depth interviews with data pioneers reveal the link between the effective use of big data and the bottom line among other results.

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Which came first, the data or the decision? This white paper makes the case for having a decision in mind, then tailoring big data's volume, variety and velocity to achieve business results such as overcoming customer dissatisfaction or creating well-informed strategies in real time.

Informationweek Reports

Research: The Big Data Management Challenge

Research: The Big Data Management Challenge

The challenge of big data is real, but most organizations don't differentiate 'big data' from traditional data, and nearly 90% of respondents to our survey use conventional databases as the primary means of handling data. We'll help you understand what constitutes big data (it's not just size) and the numerous management challenges it poses.