Big Data Solutions
Equipped with mainstream Big Data components of data collection, storage, processing and analysis, and display, providing high-performance building blocks to drive business intelligence through big data
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Benefits
Ultra-high Concurrency
Online elastic scaling on demand, without data migration to cope with performance challenges caused by super-large data volume and ultra-high concurrency requests.
Data Security and Reliability
Secure, reliable, and low-cost cloud storage services, with 99.999999999% data persistence and 99.99% service availability
Open Eco-system
Third-party tools like machine learning, algorithm modeling etc., to develop your complete Big Data Solution
Efficient Resource
Utilization: Compute and storage separation architecture can significantly reduce server cost and increase resource utilization by 50% compared to binding architecture.
Architecture
Data Lake
Big Data
Features low-cost storage of massive data, unlimited scalability, and multiple data types. It’s suitable for environmental monitoring analysis, industrial data analysis, traffic data analysis etc.
Features
·HashData uses a compute storage separation architecture, where the data is stored on the object storage, and the compute uses an MPP computing engine based on the Greenplum kernel.
·Unlimited horizontal expansion with the data access performance increases linearly to the storage capacity.
·The hot and cold data management feature of HashData ensures data query performance.
Benefits
·Compared to the compute storage binding architecture, compute storage separation can significantly reduce server cost while ensuring query requirements.
·Secure and reliable cloud storage service with 99.999999999% data persistence and 99.99% service availability.
·While ensuring data query performance, storage cost is only 1/10 of traditional solutions.
Built with mainstream big data components and basic cloud services, it provides enterprise customers with customer service analysis, log analysis, business data analysis etc.
Features
Big data cloud services based on Linux container technology (LXC), avoiding the IO loss of KVM virtualization, with performance close to bare-metal servers.
Collection, storage, and conversion of multiple data types, data structures, and data patterns on the same platform, effectively solving the data complexity challenge
Online real-time elastic scaling to enhance business processing capabilities.
Benefits
Meet customers' high-performance requirements on big data business while reducing server investment and increasing resource utilization.
Intuitive and easy-to-use one-click operation to complete the deployment of a big data cluster in minutes.
Maximizes resource utilization and to support the rapid business growth
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For more information on use cases and technical architecture, please contact our customer service team.
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