Implementing Refined Marketing at Low Costs with Game Publishers

Industry Trend — Refined Marketing of the Game Industry

The Rapid Growth of Data Volumes and Demands of Analysis

  • Scalability: The growth curve of data volumes is high, making it difficult to scale up the Internet Data Center (IDC).
  • Usability: The cost of self-maintained systems with Hadoop, Hive, and Presto combination is too high in learning and maintaining.
  • Real-Time: Due to the increasing real-time requirements of busineses, Presto, as a real-time computing engine for direct queries, fails to meet expectations. The real-time performance of data analysis is also not good enough. It is still insufficient in real-time performance, even if the direct queries are output from high-performance databases after precomputing.
  • Price-Performance Ratio: To ensure performance and stability, the cost of self-built clusters will greatly increase as IDCs scale up.

Low-Cost Solutions to Address Challenges of Growing Business Volumes

Figure 1: A Diagram of the Hadoop-Based Big Data Architecture
Figure 2: A Diagram of the Data Analysis Architecture Based on AnalyticDB
  • Fast Querying Speed: The querying speed is more than 10 times faster than online transaction processing (OLTP), and several times faster than Presto. QPS of the new platform can be changed from the hundreds level to the tens of thousands level.
  • Elastic Scaling: Nodes and configurations can be flexibly upgraded anytime as data volume increases.
  • Easy-to-Use: Almost no change cost is incurred during migration from Presto, and most MySQL migration statements are compatible.
  • Massive Scale: Nodes can be scaled up to thousands dynamically and linearly, supporting the storage and analysis of massive data.

Performance Improvements and Savings for Customers

Products Involved in This Article

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