The COVID-19 pandemic boosted player engagement in the gaming industry. Several product servers were overcrowded after the sudden burst of players. Correspondingly, the stock price of gaming companies also experienced significant growth.
At the same time, players have growing requirements for game quality. The competition in the gaming industry gets more intense in terms of game quality and in the marketing operation to gain control of the market. After considering the increasing volume costs, precision marketing became very crucial.
Company A is an innovative gaming company with over 100 million players worldwide. Company A's featured mobile game has achieved huge success worldwide. In recent years, Company A has been dedicated to developing new, high-quality mobile games and is engaged in the game publishing business to bring more games worth playing to users. Company A's game publishing platform ranks top among the Chinese mobile game publishers, helping many leading game developers publish their games worldwide.
The crucial competition in the gaming industry boosts the demand for precision marketing and real-time marketing feedback to gain time advantages. The Advertising Data Analysis Department of Company A built their own big data analysis platform based on the Hadoop system to meet the real-time data analysis demands. The explosion of data and the growth requirements on data analysis exposed the issues with this big data system:
The rapid increase of data had significant difficulties in IDC scaling.
The self-operated Hadoop + Hive + Presto system triggered the high cost of learning and maintenance.
Presto as the real-time computing engine for direct query cannot meet the growing demand for data analysis. The limit in time efficiency for data analysis was hardly broken even by directly outputting data from the high-performance database with the pre-computing process.
To ensure performance and reliability, the growth of IDC for self-built clusters brought sharply increasing costs.
Company A's big data team began to research new products and architectures to solve the issues mentioned above. After many practices with multiple open-source distributed analyzing computing engines and big data products, the requirements of the real-time and correlated query still cannot be achieved.
Company A’s Big Data Team tried to use ApsaraDB AnalyticDB for MySQL. The analytic database AnalyticDB is developed independently by Alibaba Cloud. It provides online data analysis cloud computing services for massive data real-time and high-concurrency scenarios, establishing multi-dimensional business perspectives and explorations for 100 billion data at the millisecond level. The typical features of AnalyticDB like high performance, elasticity, ease of use, scaling, and high concurrency eventually won the trust of Company A's Big Data Team. The new generation real-time gaming advertising operation analysis platform has been built based on ApsaraDB AnalyticDB by Company A’s Big Data Team and the Alibaba Cloud Database Team.
The entire solution is to input the data via logstash and store it in AnalyticDB after pre-processing. The new platform with AnalyticDB has many advantages:
10x faster than OLTP and multiple times faster than Presto; QPS from hundreds to more than ten thousand
Node and configuration can scale up/down at any time and upgrade elastically with data growth.
There is almost zero cost for the migration from Presto; MySQL migration is compatible with most of the statements.
Dynamic linear growth for thousands of nodes can support tremendous data analysis.
With the product combination of PolarDB + AnalyticDB (storage) + AnalyticDB (high-performance), Company A built a new-generation real-time data operating and analyzing platform for the gaming volume trading market. The cloud-native data processing and analysis closed-loop achieves high efficiency in gaming data operation.
The new platform brings a 5-10x analysis performance increase to boost the user experience and accelerate the conversion rate of volume marketing.
The player’s behavior logs growth of over 100 million per day and the AnalyticDB storage instance provides a cost-effective solution for clients to reduce the savings costs by 75%.
The 5-10x performance growth and 300% savings cost helped the launch of the new generation game publishing real-time data operation platform.
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