Analytics Platform for Massive-Scale Geospatial and Temporal Data
Implements data visualization based on the massively parallel processing power and graphic rendering power of GPUs. Compared with traditional solutions, ZILLIZ Analytics has higher throughput, higher cost-effectiveness, and lower latency.
Returns query results for billion-scale datasets in subseconds
ZILLIZ Analytics integrates traditional data analytics, modern data science, and intelligent workflow based on geospatial and temporal analytics into one open platform. Natively supporting SQL queries and visualized, interactive analytics, ZILLIZ Analytics is compatible with multiple mainstream machine learning models.
Thorough utilization of resources
Thoroughly utilizing the parallel processing power of GPUs/CPUs, ZILLIZ Analytics can perform SQL queries and visualized, interactive analytics on massive datasets without any pre-processing, including indexing, pre-aggregation, and downsampling, etc.
ZILLIZ Analytics unites analytics between geospatial and temporal data to help you gain a panoramic view of time and location. With fine-grained visualization of geospatial and temporal datasets, you can both view the big picture and focus on every detail.
As the data of vehicle operations and supply chain management grows fast, the logistics industry needs to make effective decisions as fast as possible to decrease fuel consumption, reduce maintenance cost, and increase vehicle utilization rate.
ZILLIZ Analytics empowers the logistics industry with the ability to analyze the whole supply chain, starting from the production line to the last kilometer in delivery. Data analysts can then analyze billion-scale datasets for vehicle operation and supply chain management in real time.Check Technique Detail
- Increased on-time delivery rate
- Optimized delivery routes by machine learning algorithms
- Geospatial and temporal analytics of vehicle operations
- Driver behavior monitoring in real time
- Real-time vehicle maintenance based on vehicle condition