An internet entertainment group is facing challenges in data processing and analysis. With the rapid growth of its business, the volume of data has increased sharply, creating an urgent need for an efficient and cost-effective data processing solution to support business decision-making and operational optimization.
Rapidly growing data volume
The company handles tens of billions of records, including user behavior logs and advertising data, putting significant pressure on storage and processing capacity.
Stringent real-time analytics demands
To stay ahead of the curve in a fast-evolving industry, the company requires timely predictive analytics on user behavior and ad performance.
Cost control urgency
As data volume continues to expand, there is a pressing need to reduce data management and processing costs without compromising performance.
System stability issues
With the increasing data volume and growing complexity of business queries, the current system is facing significant stability challenges and performance bottlenecks.
The Relyt AI-ready Data Cloud delivers a scalable, cost-effective solution through its compute-storage separation architecture. As a cloud-agnostic platform, it boosts performance with vectorized query execution and algorithmic optimization. Its Adaptive Query Scaling (AQS) feature ensures high availability and efficient management of large-scale queries, offering a powerful solution for modern data workloads.
Customer Benefits
Performance improvement
Data processing is 1176% faster, especially in ad log processing.
Cost Savings
Dynamic compute scaling doubles cost-performance in complex queries compared to traditional cloud solutions.
System Stability
Elastic computing ensures a 99.9% query success rate, even under high concurrency.
Enhanced Business Insights
Real-time queries and efficient batch processing boost insights and performance in large data handling.
90%
deduction in ETL costs
10x
query latency optimization
Real-time queries
Multidimensional analytics