TimeWizard
PraveenPraveen
Overview Impact on OLTP Applications
Audience: Forecasting the problems with increased
user’s activity on net and increased gadgets that can connect to net
Compliance Requirements Social Networking evolution Types of data and volumes of data being
stored.
Curtain Raiser
Impact on OLTP Applications With the Pace and Volume Growth(s), It has
become difficult to maintain the response-time and still maintain the data for the duration dictated by law(s) and statuary requirements
In the timely manner,Timewizard fills the gap.
Features & Benefits Database Stimulator:
It extends the capacity of OLTP Systems to store more data than what it currently supports.
Ex: Currently, your system supports 2 million data (or 2 years), after which,OLTP system transfer the data to DW and Purges the data from OLTP.
With the adoption of Timewizard,the same system supports 5 million data , which is equivalent of 5 years as per the linear growth.
Features & Benefits Database Accelerator:
It extends the capacity of OLTP Systems to respond more quicker than what it currently supports.
Ex: Currently, your system supports 2 million data (or 2 years), and consumes 2 minutes to retrieve the data, and beyond the threshold of 2 million,OLTP application times out.
With the adoption of Timewizard,the same system supports and consumes 5 sec to retrieve from same 2 million data.
Features & Benefits Database Explorer:
Combining the benefits of database stimulator and accelerator,it extends the scale-up capacity of OLTP Systems to differ the need for scale-out requirements.
Ex: Currently, your system supports 2 million data (or 2 years), and consumes 2 minutes to retrieve the data, and beyond the threshold of 2 million,OLTP application times out.
So,either you need to add more processors or add more nodes to the current configuration of the system to support more volumes
With the adoption of Timewizard,the same system supports and consumes 40 sec to retrieve from increased 5 million data.
Applications Large User Base:
Banking Applications Finance Applications Insurance Applications
Huge Activity Base: Social Networking apps Messenger/chat apps
Longer Data Retention period Base: Legal applications
Specifications
For Banking applications:
Ex:you need to get all the transactional details for past 3 years from your account.
But, Most of banks support this feature for 18 months with the batch size of 6 months each.
With the adoption of timewizard, existing OLTP can support the req.
Specifications For finance applications: (stock trading application)
Ex:you need to get all the transactional details
for past 3 years from your account.. But, Most of
applications support this feature for 1 month with the batch size of 1 month each.
With the adoption of timewizard, existing OLTP can support the req.
Features and Benefits SummarySno Feature Description Example
1. DB Stimulator Support for increased large volumes of data.
Your current system, till now, supports for 2 million rows on transaction table.
With the new model,It supports 5 million data.
2. DB Accelerator Support for quicker response time.
Your current system consumes 2 min to
render the report of 2 million rows.
Now, it takes less than 30 sec to render the same data.
3. DB Design Extender Facilitates the capabilities of aggregate tables on
OLTP system itself.
You can build and populate aggregate tables after finding breakeven point of supporting volumes.
Read the benefits in conjunction with (1)
4. DB Synchronizer Acts as platform by providing common storage pattern across database products.
By adopting the common storage pattern , numeric representation of dates,
Direct comparison of data is possible across SAP and SQL server.
Few facts- Performance statisticsReport Name Metric Original Query Option A Option B Option C
Execution Time(in milliseconds)
CPU Usage
IO Usage
Execution Time(in milliseconds)
CPU Usage
IO Usage
Execution Time(in milliseconds)
CPU Usage
IO Usage
Comparative facts- Performance statisticsReport Name Metric Crystal
Reports
Others1 Others2 Timewizard
Execution Time(in milliseconds)
CPU Usage
IO Usage
Execution Time(in milliseconds)
CPU Usage
IO Usage
Execution Time(in milliseconds)
CPU Usage
IO Usage