SAP HANA & ORACLE EXALYTICS

White Paper - Business Data Warehouse

Sunny Sarin

Chirag Saraogi

Jagruti Dwibedi

Neharica Sharma

Pramil Mittal

SAP HANA & Oracle Exalytics

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Topic Page #

Executive Summary 2

Introduction 3

Background 3

Premise 4

Comparison 6

SAP HANA: Other Issues Addressed 9

Conclusion 10

References 11

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Executive Summary

A study found that “High performance businesses” are five times more likely to use analytics to resolve

their business challenges by turning high volumes of data into actionable insights that can enable them to advance their business objectives, achieve their revenue goals and sustain a competitive advantage. The key to successful analytics is gaining timely insights from data that ultimately leads to better decision making.

Having a range of products in business analytics segment, today we are providing our analysis to choose between Oracle Exalytics and SAP HANA, the leading tools in data analytics.

Data is changing very quickly today at a rate which was not anticipated a decade ago. A study shows that on average companies around the globe have data which is increasing at 50% per year and price of the Technology used to store this data is decreasing at 30% per year. This disparity in speed is making data

the biggest concern to businesses today. When analyzing the tools used to perform analysis on this data, important factor to cater is the platform used to work with the data rather than the method of storage used.

This Whitepaper is intended to explicitly articulate this insight by analyzing, exploring and comparing the two data analytics giant in the industry – SAP HANA and Oracle Exalytics.

The factors that we have considered in our comparison are among the factors most important to the Organization when it comes to making a final call on which Appliance / tool should be used.

We have taken care that the tool that stands out in the comparison will not only be the best performer

in terms of our comparison parameters but will also be functionally laden with the latest technologies and resources.

Since the basic goal of any technology or appliance is to have an optimum cost in terms of implementation, TCO, deployment ,support and ease of use for the resources. We will be revolving around these factors primarily for our comparison between the two.

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Introduction

This Whitepaper is an Exploration, Analysis and comparison between the Data Analytics Power Houses in the Industry – Oracle Exalytics and SAP HANA. In particular it may be argued that one Database appliance is better than the other in some factors.

The comparison is made on various aspects and factors like ease of use, TCO, Cost related to Implementation, Support, Maintenance, Initial training to resources, deployment and many other such factor and then show some of the benefits of using SAP HANA over Oracle Exalytics.

HANA and Exalytics – Background

SAP HANA

There has been some confusion over exactly what SAP HANA is, so let's go there first. SAP HANA, first

and foremost, is a full transactional relational database management system (RDBMS). It is ACID-compliant, which means it is fully resilient against hardware failure (it uses save points and logs to save

information to disk). It supports disaster recovery and fault tolerance. It is moderately scalable for large

workloads (16 TB of compressed data, 80 TB+ of comparable Oracle) and it is available as an appliance from the major hardware vendors (Cisco, Dell, Fujitsu, HP, Hitachi, IBM and NEC).

But SAP HANA is unlike any other RDBMS. First, it is fully in-memory: When you start it up, it loads the data into RAM. It has both row stores and column stores, which means it can support transactional (OLTP) and multidimensional (OLAP) workloads. All of its OLAP capabilities are virtual; you don't need to

duplicate data or have a separate system for reporting. It doesn't require caches, aggregation, indexes or physical cubes, although some of these performance features are supported if you really want them.

Because it stores data just once, you can push data into it in real time using tools, such as SAP Landscape

Transformation, Data Services or Event Stream Processing for transactional purposes, and report off it at

the same time. In addition, it has a number of memory-resident features, including support for OLAP

and planning engines of Net Weaver BW and a predictive analytics library (PAL) that allows statistical analysis over billions of rows of data in real time.

Oracle Exalytics

Oracle Exalytics is a clever box. It is a good supplement to an existing Oracle RDBMS or Oracle Exadata

database machine. It is a collection of disparate technologies including the TimesTen in-memory database, Essbase OLAP engine and Oracle BI Foundation front-end tools.

It can automatically suggest parts of the Oracle database to replicate into its "smart cache," which is

basically an aggregation engine. Then your BI queries will run against either Exalytics or Oracle. So while there isn't anything wrong with Exalytics (and if you want to accelerate your existing Oracle database it could be a great solution), comparing Oracle Exalytics with SAP HANA is banal.

Oracle does a lot of what in the retail trade are called “knockoffs.” They think this is good business, and we think they’re right. The pattern is simple. When someone creates a product and proves a market, Oracle (or for that matter SAP) creates a quite similar product. So, when VMWare and others prove

Vsphere, Oracle creates Oracle VM, when Red Hat builds a business model around Linux, Oracle creates “Oracle Linux with Unbreakable Enterprise Kernel.”

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The knockoffs or more technically OFPs for “Oracle Follow-on Products”–are usually feature-compatible with the originals, but have something, some edge, which Oracle claims makes them better.

Going in, we usually expect that Oracle is offering pretty much what you see at JCPenney’s or Target, an acceptable substitute for people who don’t want to or can’t pay a premium, want to limit the number of vendors they work with etc.

That is what one would expect in any market. After all, if you buy an umbrella from a sidewalk vendor

when it starts to rain, it’s a good thing and it’s serviceable, but you don’t expect it to last through the ages.

Of course, with software, it’s much more confusing than it is with umbrellas.

When SAP released HANA, an in-memory database appliance, Oracle has released Exalytics, an in-memory database appliance.

SAP HANA & Oracle Exalytics – Premise

HANA: The Features that Matter

Oracle Exalytics and SAP HANA have three things in common. Both are in-memory databases, both are appliances and both can serve analytic workloads. The similarity ends there.

We will temporarily step back from phrases like “in-memory” and “analytics,” because now both SAP and Oracle include these functionalities and look instead at the underlying problem that “in-memory”

and “analytics” are trying to solve.

There are certain problems associated with our premise:

Problem 1. The traditional row-oriented database is great at getting data in, not so good at getting data out.

Problem 2. The various “analytics databases,” which were designed to solve Problem 1–including, but

not limited to the column-oriented database that SAP uses–are great at getting data out, not so good at

getting data in.

Problem 3. Cost of implementation, training and usage associated with both the database appliances.

What you’d really like is a column-oriented (analytics) database that is good at getting data in, or else a row-oriented database that is good at getting data out.

HANA addresses this problem in a really interesting way. They made a database where you get to choose

how to treat the data, as either row-oriented or column-oriented. (If you want, imagine there’s a software switch that you can throw.) So, if you want to do something that requires read-optimization, that is, the very fast and flexible analytic reporting that column-oriented databases are designed to do, you throw the switch and in effect tell HANA, “I want to run reports.” And if you want to do something

that requires write-optimization, like doing the transactions that row-oriented databases are designed to do, you throw the switch and tell HANA, “I’m entering a transaction.”

Underneath, the data is the same; what this imaginary switch throws is your mode of access to it.

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“In effect, it’s a trans-analytic database.” How do they make the database “trans-analytic?” Effectively,

they use the in-memory capabilities to do the caching and re-indexing much more quickly than would have been possible before memory prices fell.

There’s one other big problem that the in-memory processing solves. In traditional SQL databases, the only kind of operation you can perform is a SQL operation, which is basically going to be manipulation of

rows and fields in rows. The problem with this is that sometimes you’d like to perform statistical

functions on the data: do a regression analysis etc. But in a traditional database, statistical analysis (or

sometimes even simple numerical calculations) can be complicated and difficult.

In HANA, though, business functions are built into the database. So if you want to do a forecast, you can just run the appropriate statistical function. It’s less cumbersome than a pure SQL database. And it’s very, very fast. There are improved performance improvements of three orders of magnitude.

Exalytics: the Features that Matter

Now when we point out that HANA is both row-oriented (for transactions) and column-oriented (so that it can be a good analytics database) and then we point out that it has business functions built-in, we are not yet making any claim about the relative merits of HANA and Exalytics.

Well because it turns out that with Exalytics, too, you can enter data into a transaction-oriented database and you can do reporting on the data in an analytics database. And in Exalytics, too, you have a business function library.

But the way it’s done is different. In Exalytics, the transactional capabilities come from an in-memory

database (the old TimesTen product that Oracle bought a little more than a decade ago). The analytics capabilities come from Essbase (which Oracle bought about 5 years ago), and the business function library is an implementation of the open-source R statistical programming language.

So, Oracle would argue, it has the same features that matter. But, Oracle would also argue, it also has an

edge, something that makes it clearly better. If you get Oracle’s Exalytics, you’re getting databases and function libraries that are tested, tried, and true. TimesTen has been at the heart of Salesforce.com since its inception. Essbase is at the heart of Hyperion, which is used by much of the Global 2000. And R is used at every university in the country.

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HANA and Exalytics - Comparison

In HANA, all the data is stored in one place. In Exalytics, the data is stored in different places. So, in

HANA, if you want to report on data, you throw that (imaginary) switch. In Exalytics, you extract the data

from the TimesTen database, transform it, and load it into the Essbase database. In HANA, if you want to run a statistical program and store the results, you run the program and store the results. In Exalytics, you extract the data from, say, TimesTen, push it into an area where R can operate on it, run the program then push the data back into TimesTen.

We can guess that moving data takes time. Since the databases involved are not perfectly compatible, one needs to transform the data as well as move it. (Essbase, notoriously, doesn’t handle special

characters, or at least didn’t use to.) Because it’s different data in each database, one has to manage the

timing, and one has to manage the versions. When you’re moving really massive amounts of data

around (multi-terabytes), you have to worry about space. (The 1TB Exalytics machine only has 300 GB of actual memory space.)

One thing you can say for Oracle. They understand these objections, and in their marketing literature,

they do what they can to deprecate them. “Exalytics,” Oracle says, “has Infinity band pipes” that presumably make data flow quickly between the databases, and “unified management tools,” that presumably allow you to keep track of the data. Yes, there may be some issues related to having to

move the data around. But Oracle tries to focus you on the “tried and true” argument. It essentially says,

if you have to move the data between containers, when each of the containers is so good, so proven, and has so much infrastructure already there, ready to go.

Oracle has tried to publicly compare Exalytics pricing to HANA and the information presented is grossly misleading. Not only is SAP HANA less expensive in up-front cost than Oracle’s Exadata + Exalytics

bundle, (plus all the derivative components you’ll need to make it work) the differences in total cost of ownership are substantial.

SAP didn’t just innovate on the technology platform with SAP HANA, they innovated on pricing as well with a straightforward, simple to understand model based solely on the amount of data held in memory

(Unlike Oracle which charges per CPU plus test and development environment fees.) A single unit of

HANA (1 HANA unit = 64 GB of RAM) includes the FULL production, test and development licenses a

customer needs. It also includes the data modeling and management tools needed to get data into HANA and actually use the product. Even better, HANA gets cheaper over time and the more you buy, the more the list price per unit reduces.

SAP customers running SAP Business One can purchase a HANA license for as little as €2K. Any customer

can purchase a license of SAP HANA Edge Edition for €40k. We also have the SAP HANA Net weaver BW edition for as little as €13k per HANA unit. (64GB of RAM = 1 unit)

We are certain Oracle would cite that hardware is extra, so let’s cover it right now. HANA servers from certified partners like Fujitsu are available for as little as $12K. That’s because SAP doesn’t force its

customers into one hardware stack and then overcharge for it. SAP have certified partners like IBM, HP,

DELL and the list goes on and on for HANA. We believe that the Intel platform, combined with the continued commoditization cycle we’ve seen for the last 40 years in computing will win.

Even with rapid growth of data, 95% of enterprises use between 0.5TB – 40 TB of data today. For this market, at the low end (0.5 TB) the combined cost of hardware and software is approximately $500K

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and at the high end the pricing is comparable to Exalytics alone today. In a recent test SAP ran a 16 node

cluster of 100 TB of uncompressed data.

HANA: The Design Idea

In TimesTen or Essbase or other traditional databases, the design idea is roughly as follows: if you want

to process data, move it inside engines designed for that kind of processing. Yes, there’s a cost. You might have to do some processing to get the data in, and it take some time. But those costs are minor,

because once you get it into the container, you get a whole lot of processing that you just couldn’t get otherwise.

This is a very normal, common design idea. In HANA, there’s a different design idea: Don’t move the

data. Do the work where the data is which makes it all a lot easier, convenient, flexible and more reliable.

Now, consider what HANA’s far more extensive capabilities do for that example. First of all, in HANA, data can be imported pretty much continuously. Second, in HANA, we can use the business functions to do some statistical analysis of the gate delay times. So instead of columns of times, we will get a single, simple output containing the probability of a delay at each checkpoint. We can do everything at one

place. And this gives us better and more reliable information.

So What Makes It Better?

The core difference between HANA and Exalytics is that in HANA, all the data is in one place. Here is why:

When we see a new design idea–and we think it’s safe to say that HANA embodies one of those–we would like to apply two tests. Is it simplifying? And is it fruitful?

So what about HANA? Simplifying and fruitful? Well, let’s try to compare it with Exalytics. Simplifying? Admittedly, it’s a little mind-bending to be thinking about both rows and columns at the same time. But

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when you think about how much simpler it is conceptually to have all the data in one database and think

about the complications involved when you have to move data to a new area in order to do other operations on it, it certainly seems simplifying.

And fruitful?

It took us a long time to figure out a point, where Exalytics helped us that when we started comparing the business function library to the “Advanced Visualization” Oracle was providing. When it came to statistics, they were pretty much one-to-one; the HANA developers very self-consciously tried to incorporate the in-database equivalents of the standard statistical functions, and Oracle very self-consciously gave you access to the R function library.

But the business function library also does business functions, like depreciation or a year on-year

calculation. Advanced Visualization doesn’t.

This is important not because HANA’s business function library has more features than R, but because

HANA is using the same design idea (the Business Function Library) to enrich various kinds of database

capabilities. On the analytics side, they’re using the statistical functions to enrich analytics capabilities. On the transaction side, they’re using the depreciation calculations to enrich the transaction capabilities. For either, they’re using the same basic enrichment mechanism.

And that’s what Oracle would find hard to match. Sure, they can write depreciation calculation functionality; they’ve been doing that for years. But to have that work seamlessly with the TimesTen database, they’d have to create a new data storage area in Exalytics, with new pipes and changes in the

management tools.

SAP HANA: Other Issues Addressed

Operational Reporting: Leveraged SAP HANA as a scalable platform for Artist operational reporting of SAP

and non-SAP data sources offering fast loading through real time replication, fast report generation and

flexible navigation options with reduced administration effort. It offers new possibilities of analyzing big

data of any format with the end goal to eventually provide customers self-service reporting capabilities

on KPIs and to allow status tracking in real-time.

Optimized profitability: Sales & Marketing representatives face the challenge to identify the “value” of

each Artist derived from sales, granted discounts, etc. In order to provide recommendations on what to

offer each Artist for sales growth. Additionally, Sales & Marketing organizations need to analyze

promptly several millions of Artist data from several data sources. There is a lack of a visualization,

exploration and predictive analytics to support intelligent decision making through meaningful KPIs and a

full view of Artist data.

Overall SAP HANA Rating (8/10)

HANA is used as:

• A data base for our OLTP system.

• A data base for Our OLAP System.

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• A Data warehouse.

• Analytic engine for BI

SAP HANA: Pros

• Optimized profitability

• Operational Reporting

• Real Time Inventory Management

• Sales Analysis

• Profitability

SAP HANA: Cons

• GUI

• integration with SAP BI

• Integration with SAP BOBJ

SAP HANA: ROI

• Faster Decision making

• TCO on IT reduced by 70%

• Increased Data Analysis

• Brought Business closer to real time data

HANA & Exalytics: Customers

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Conclusion

Should we invest on a SAP HANA or Oracle Exalytics? Current SAP customers should strongly consider deploying SAP HANA to add real-time analytical and transactional processing capabilities on top of existing SAP ERP and other business systems deployment. Non-SAP customers unsatisfied with their current EDW environment should also evaluate

HANA, weighing the benefits of adding near real-time analytical capabilities against the cost of migrating to a new system and new vendor. It is also important to evaluate where real-time analytics

will most benefit your enterprise. Not all business problems can be solved via real-time analytics, and systems such as HANA should only be deployed where significant business value can be achieved. Among the important differences compared to SAP HANA, Exalytics is designed to run on Sun-only hardware, it is a mash-up of various existing Oracle technologies, and there are few, if any, systems in

production. As with all Oracle technologies, the risk of vendor lock-in is high, and the cost is significantly higher than comparable HANA deployments.

Each is aiming at a specialized market within the IT universe. Despite SAP's greater focus on

transactional applications, both SAP and Oracle are looking at largely the same customers. These

customers are firms that need high horsepower appliances and are willing to spend in millions on the hardware and software capable of meeting their needs.

Our findings have drawn us to the conclusion that signing up for Oracle’s Exalytics parade and its never

ending set of hardware purchases, licenses and maintenance will increasingly lock-in control over the Organization and its future ,with antiquated architectures. SAP’s focus on innovation, with solutions like

SAP HANA, feature a simplified architecture, fewer layers, more choice of hardware partners and vastly

greater performance, all at significantly lower cost of ownership (TCO).

The bottom line: HANA is a next generation solution that replaces many of the tired, legacy products

that Oracle continues to re-label as “INNOVATIVE”.

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References

Websites http://www.sap.com/hana

http://experiencesaphana.com/ http://scn.sap.com/community/hana-in-memory

http://scn.sap.com/community/hana-in-memory/blog/2012/03/17/sap-hana-versus-oracle-exalytics

http://www.news-sap.com/oracle-exalytics-old-wine-in-new-wineskins/#sthash.1b5hFcFs.dpuf

https://blogs.saphana.com/2012/04/30/what-oracle-wont-tell-you-about-sap-hana/

https://blogs.saphana.com/2014/01/30/ceo-implementing-sap-erp-today-on-sap-hana-in-the-cloud/

Blogs

Excerpts from the Blogs by Mr. Vishal Sikka, former Executive Board Member for Products and Innovation, SAP

Excerpts from the Blogs by Bill McDermott, CEO, SAP

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