Red3i speeds insights by 1,000X with MySQL HeatWave

Digital marketing firm accelerates media and advertising insights by 1,000X and saves 60% in costs using MySQL HeatWave on Oracle Cloud Infrastructure.

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تحديات الأعمال

Red3i provides business intelligence by acquiring, analyzing, and processing media data better to help clients improve customer acquisition through multichannel marketing campaigns, online and offline. Helping clients understand the digital marketing landscape and the performance of their marketing campaigns requires using quality data for real-time intelligence, historical trend analysis, detailed segmentation, and predictive modeling. 

The marketing agency was using AWS Aurora for a mission-critical processing platform for 6 TB of ever-growing data. However, the company discovered that running analytics queries to gauge marketing campaign performance took too much time and effort because data had to be transferred to a separate relational database. Expenses and complexity were rising for the company, along with demand for data and insights from clients to increase return on advertising investments. 

Why Red3i Chose Oracle

After evaluating Google BigQuery, Snowflake, and AWS Redshift, red3i migrated from AWS Aurora to MySQL HeatWave on Oracle Cloud Infrastructure (OCI) to significantly accelerate analytical queries, reduce costs, and improve ease of use. MySQL HeatWave easily enables red3i staff to run OLTP and OLAP workloads directly from the MySQL database in-memory, eliminating the need for data movement and integration with a separate analytics database.  

النتائج

Using MySQL HeatWave increased complex queries for red3i by as much as 1,000X for real-time analytics and by 85% for overall workloads without changing code to its applications. IT costs dropped by 60% by eliminating multiple middleware tools and analytical platforms. Automatic recovery minimized downtime for high availability. 

Scalability from MySQL HeatWave enables red3i to scale its ever-growing 6 TB database from its cluster of 12 nodes to thousands of cores at constant costs and administration.

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