Veritix Created Competitive Advantage Using Attunity and Amazon Redshift
Company Size
200-1,000
Region
- America
Country
- United States
Product
- Attunity
- Amazon Redshift
Tech Stack
- Oracle
- Microsoft SQL Server
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Cost Savings
- Productivity Improvements
Technology Category
- Infrastructure as a Service (IaaS) - Cloud Computing
- Infrastructure as a Service (IaaS) - Cloud Storage Services
Applicable Functions
- Sales & Marketing
Services
- Cloud Planning, Design & Implementation Services
About The Customer
Veritix (now part of AXS) specialized in digital ticketing, event marketing, and relationship management applications for professional sports teams, artists, and entertainment venues around the world. With their analytics reporting, their customers can target demographic groups more effectively, improve season ticket renewal rates, and bring new fans into arenas.
The Challenge
Veritix’s transactional database was used for both production purposes and reporting. As a result, it wasn’t optimized for analytics and performance was a concern. Running analytics on the production machine would have overwhelmed system resources. Rojas’ team decided to create a separate data warehouse which would store a decade of event data, as well as additional information to enrich analyses such as weather, drive times, and fan income. The project goals were twofold: to develop a high-performance analytics data warehouse and to tune the existing production database for transactions. Veritix was primarily using Oracle, but they also had some Microsoft SQL Server databases. As they looked to expand their data warehouse, they performed a cost analysis of a traditional, on-premises data warehouse and found that it would cost millions to achieve the performance levels that they required.
The Solution
Veritix looked to the cloud for a solution. By doing a series of cluster tests on Amazon Redshift, they found that the cloud-based data warehouse could deliver the performance that the company needed while supporting multiple database vendors. And, Amazon Redshift pricing was an order of magnitude less expensive than the other solutions they looked at. After deciding to move forward with an Amazon Redshift data warehouse, Veritix began exploring ways to replicate data from their on-premises databases to the cloud. Initially, the team assumed that they would need to build custom tools or rely on an off-the-shelf solution like Microsoft SSIS. They did an initial experiment which started with the team creating a backup. Then they moved it to the cloud, restored the backup to a staging database, and tried to move the staging database to Amazon Redshift. Veritix was disappointed to find that it took seven hours to transfer the data, plus an additional 14 hours to restore it to the staging database. This approach was so time consuming that it would only be possible to move information to Amazon Redshift once a day. One of Veritix’s data scientists mentioned the challenges to the team at Amazon Web Services who recommended Attunity for the job.
Operational Impact
Quantitative Benefit
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