First Independent Benchmark of Spatial and Time-Series Databases
Organizations are increasingly incorporating geospatial data to assess data trends that are often difficult to see. Combing geospatial data with real-time and IoT data adds a layer of analytics capability that can help companies unlock more profound insights, provide a complete picture of behaviors, develop new lines of business for a competitive edge, and improve operations such as marketing and customer service.
Analyzing location-enriched IoT and time series data still presents new challenges to data analytics practitioners and vendors. Spatial and time-series analysis requires non-traditional joins, filters, and specialized analytic functions. Despite the growth in data volumes and commercial interest, there was no framework in the marketplace to help organizations evaluate database technologies suitable for these workloads.
This exciting webinar will offer an opportunity to learn about a new independent Space and Time Benchmark research assessing the performance of leading databases.
Join in this interactive learning session to understand –
- Business questions and scenarios that require spatial and time-series data as the basis for the benchmark study
- Database SQL feasibility for analyzing geospatial and temporal data
- Working with relational and native graph databases, streaming data, and in-database visualizations
- Performance results and factors that impact business analysis