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Sybase IQ as a Data Warehouse with BI : ASUG Webcast

There was a tweet from Jon Reed about a question at SAP TechED Madrid, asking if SAP Hana and Sybase IQ are like Woody Allen’s movie “Hannah and Her Sisters”.    It reminded me of this great webcast from late August of last year, which I will summarize below. 

This was an ASUG webcast that SAP’s Balaji Krishna and Yuvaraj Raghuvir provided to ASUG last year.  The information may have changed since this webcast and of course the usual disclaimer applies, the information is subject to change.


On the agenda:

  • Sybase IQ positioning
  • Why SAP BusinessObjects & IQ Together
  • Integration points for IQ and BusinessObjects BI


We have an information explosion; an explosion of information and speed with which business needs to react.  In a perfect world  the information would be current and complete so business decisions are most accurate and looking for an immediate answer.  It has been expensive to improve performance  – the  information access, complex systems, duplicating information, lengthy validation approval process

Sybase IQ is open, ANSI SQL compliant.  It has data compression, is columnar, it is easy to compress and can get real time feeds with Sybase Replication server


Figure 1, Source: SAP


As Figure 1 shows the lowest layer is the Data Warehouse with volumes of data.  EIM turns data into quality information you can trust.  BI “turns data into insight”.


Figure 2: Source, SAP


Figure 2 shows several options with SAP Data Warehousing and analytical databases.  SAP says “complement” each other.  All offerings have been integrated with BusinessObjects and EIM for analytical reporting initiatives.  The right side of Figure 2 shows the offerings.


Figure 3, Source: SAP

Figure 3 shows a “paradigm shift”, where we are moving from a rear-view to a windshield approach to look forward to make better decisions.  Analytics is everywhere. 

The right side of Figure 3 shows the scenarios such as calculating profitability of millions of customers everyday.


Figure 4: Source: SAP

Traditional warehouses cannot get to the new paradigm such as senior management not getting the information they need and manual analysis in Excel and Access.


Figure 5, Source: SAP

Sybase IQ has more than 1900 customers as shown in Figure 5.  It is mature, offering data compression and  “moves data closer to the user”

Examples are shown on the right of Figure 5 including analyzing all federal tax returns in the US.


Figure 6, Source: SAP

Figure 6 shows “what the analysts say”.  What it means – distributed query processing in 15.3 and 15.4 – federated across storages

Federated analytics – Sybase IQ is able to do a distributed query across multiple node storages.


Figure 7, Source: SAP


What is under the hood of Sybase IQ.  It is designed for analytics “from within”. 

Each column is stored separately, with a unique column based.  It is ANSI SQL compliant

Queries are flexible and ad hoc.  Optimized storage with terabytes of information, queries with only columns used means save on # of CPU’s  and storage.  It supports any data schema.  It is designed “internally to suit analytical performance”.


Figure 8, Source: SAP


How does this fit into overall business analytics with SAP?

In the area of event processing and data replication there are Sybase products (Sybase Replication Server), coming together with SAP BusinessObjects Data Services.


Figure 9, Source: SAP


Figure 9 shows some leading use cases for Sybase IQ such as organizations with overburdened transaction systems.  It involves a proof-of-concept to show how IQ can add value using customer’s data.  It is a complementary solution.   

Advanced analytics requires sophisticated processing and see an advantage of Sybase IQ.  Web based shops want to provide analytics to end user (scenario 4 in Figure 9).


Figure 10, Source: SAP


Figure 10 shows accelerated reporting systems with a variety of data sources (on the left).  There are different options and then offload reporting data to Sybase IQ.


Figure 11: Source, SAP

Figure 11 shows moving from the source system to the data warehouse, VLDB scaling and deep analysis, the columnar store allows for speed for complex queries.  It includes tools to support decision-making and visualization, using IQ as a data mart .  It is a centralized data warehouse, using federated data marts, consuming other sources of information.


Figure 12, Source: SAP


Figure 12 shows an example of data compression using 1 TB of data in a database, need to build indices which take up space.  You need to build summary tables, which adds more space.

With Sybase IQ, few indices need to be built.  Using the same data, Sybase IQ will store it in less than a TB


Figure 13: Source, SAP


Figure 13 shows how you can use the text index and third party plug-ins

Text Search, Text Analytics and Text mining are some of the add-ons, to combine text analytics with in database.


Figure 14, Source: SAP


On the left you have Data Quality, Data Services, Data Profiling, use to load from multiple data sources on to Sybase IQ

Complex Event Processing (CEP) engine that comes with Sybase IQ used for Operational BI reporting on transactional data

On the right you see the SAP BusinessObjects BI which work with Sybase IQ, all from a single vendor.


Figure 15, Source: SAP


Figure 15 shows BusinessObjects and Sybase IQ integration and key integration points to ensure that IQ works best with BusinessObjects

Data Services can load from multiple data sources, load to IQ, and use BusinessObjects reporting.

Integration surrounds BusinessObjects Data Services and BI platform to optimize integration points

Data Services has the  kind of “push downs” to IQ faster and better

BI on the front end: what can be done from a semantic layer with Sybase IQ.


Figure 16, Source: SAP


Key value proposition with Data Services is ways to move data and improve the quality of data, ensure that data is in place.  Text Data Processing is extraction based on unstructured data.


Figure 17, Source: SAP


Figure 17 shows that SAP wants Data Services to be the best ETL for Sybase IQ, so IQ can be loaded fast

It calls all the high performance API’s to load data at a faster rate, using Data Quality algorithms from Sybase IQ  and integrating Data Quality Libraries in Sybase IQ inside the Sybase IQ kernel.


Figure 18, Source: SAP


Reporting with BI platform provides for visualization; Sybase IQ ODBC JDBC drivers to act “seamlessly”


Figure 19, Source: SAP


BI platform has access directly to Sybase IQ.  Discovery and analysis is fast, and response time is fast.

Modules have direct access to IQ with no intermediate layers.

Semantic Layer/Universe Layer  ensures the various questions and exploration queries – IQ must understand how Semantic Layer works . 

Schemas – semantic layer to understand IQ as a special repository – schemas and security, access controls


Figure 20, Source: SAP


Figure 20 shows they will certify and support different versions and “optimize the BI products”


Question & Answer

Q: In SAP implementation (which has ECC and BW), how would you compare ‘SAP BW on HANA’ with ‘Sybase IQ’. Earlier without HANA in picture, moving data from BW to SybaseIQ made sense but now it’s little confusing. Please clarify.


A: We have a use case where you can use HANA in conjunction with IQ (for aging data). BW along with IQ offers a smart storage solution that builds on top of the BW’s Near Line Storage option. Large volumes of data in BW can now be tiered into IQ. IQ can simultaneously provide analytics directly on the data loaded into it. The use cases are (1) BW with IQ via the NLS and (2) HANA as high value operational data mart along with IQ for aged data analytics.


Q: How expensive they are in comparison to other databases like DB2, Oracle, SQL server etc and above all HANA a SAP product.

 A:  IQ is cheaper than any of the others  mentioned and is used only for OLAP…its not a transaction DB

Q: What are the performance stats between Sybase IQ and HANA?

A: HANA is much faster (refer to the metrics published under than IQ plus HANA provides real time analytics.


Q: How does BI connect to IQ: relational model or MDX model?

A: relational

Q: From an ETL and modeling perspective, BW is time-intensive.  How does Sybase IQ/Data Services compare?

A: BW – benefits of complex queries in OLAP.  Sybase IQ is more relational.  Data loading is faster, doing the transformations in Data Services.  Cannot say which is better.


Our thanks to Balaji and Yuva for supporting ASUG with this webcast.  I hope we learn more at ASUG Annual Conference in May.

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      • Tammy, you doing great things – distribute information about the world. Thank you.

        I am played last week with IQ 15.1, with random queries on table with 4,6B rows – max response time – less than min. Not bad isn’t it).

        • But there one but – price…

          IMHO – Price for IQ inadecvate.
          Big bosses from sap and sybase must think about more flexible price politics for IQ, if they realy want to populize this db.

  • Thanks for the interesting post Tammy. I am currently investigating using HANA as our hosted analytics platform for our multi-tenant customers but without replacing the transaction SQL Sevrer database as this would be a huge job. SO sometimes I think using HANA just for analytics may be a bit of a sledgehammer to crack a nu tif you know what I mean.

    So IQ may be another good option as if we are having to move our data from the transactional database to an analytic database IQ is another option to HANA.

    I was wondering if you had any views on this?



    • Christian,

      Thank you for reading.

      As I have never used IQ I am not sure I can give any informed views or opinions on this.