SafeGraph optimizes geospatial data processing with Databricks and Delta Sharing
SafeGraph used the Databricks Data + AI Platform, Delta Lake, Delta Sharing and MLflow to process petabytes of geospatial data and feed predictive models, achieving 2x-10x faster spatial querying, indexing and partitioning and a 50% reduction in peak memory consumption compared to other platforms, while reducing data access time for partners from months to minutes via Delta Sharing.
Overview
SafeGraph used the Databricks Data + AI Platform, Delta Lake, Delta Sharing and MLflow to process petabytes of geospatial data and feed predictive models, achieving 2x-10x faster spatial querying, indexing and partitioning and a 50% reduction in peak memory consumption compared to other platforms, while reducing data access time for partners from months to minutes via Delta Sharing.
This entry has 13 published fields tied to exact passages in an immutable source capture.
Inspect the highlighted sourceThe challenge
Working with petabytes of historical geospatial data, SafeGraph's lean team of engineers was challenged with massive volumes of data and incomplete data sets; processing high volumes of information while accurately analyzing the nuances of each data set was time-consuming and resource-intensive, and the team found that cloud storage was not an ideal place to write or manage such massive data sets.
The solution
SafeGraph built its analytics system on the Databricks Data + AI Platform, using Delta Lake as the foundation to unify data sets and build scalable data pipelines feeding analytics and machine learning models, Delta Sharing to securely exchange large data sets with customers and partners, and MLflow for predictive model deployment, monitoring and performance tracking, alongside AWS Redshift, EKS Kubernetes, and Elasticsearch.
Reported business value
SafeGraph achieved 2x-10x faster spatial querying, indexing and partitioning, and a 50% reduction in peak memory consumption compared to other platforms; adopting Delta Sharing also reduced data-exchange access time from months to minutes for customers and partners.
Sources
Open any source and check the claim yourself — that is the point of the register.
This record was researched and written with AI assistance, and its claims were checked against the sources above. (EU AI Act art. 50 transparency notice.)
Other technology & software entries in the register.
HP crafts marketing campaigns that resonate with customers using Databricks and Uniphore
HP centralized first-party customer data on the Databricks Data + AI Platform with Delta Lake and Unity Catalog, and connected it to Uniphore's HybridCompute for federated query pushdown, cutting campaign setup from 2 weeks to 2 hours and processing 400 million records in seconds.
Building a safer and more sustainable world
Novade, a construction management software company, partnered with Databricks to modernize its analytics and ML infrastructure, moving from a homegrown Apache Airflow stack to the Databricks Data + AI Platform with Delta Lake, Unity Catalog and MLflow. The move reduced total cost of ownership by 60% and supported a 100% increase in new clients, while enabling ML models for predicting incident risk affecting worker safety and project delivery schedules.
Transforming Weather Forecasting with Lakeflow Jobs
AccuWeather migrated from on-premises infrastructure to Databricks and Lakeflow Jobs, working with Datadog for observability, to unify diverse weather data formats and orchestrate 4,500+ weekly jobs. Lakeflow Jobs coordinates the ingestion of multiple weather models, triggers machine learning processes that weight and blend different forecasts, and manages complex job dependencies for reinforcement training workflows used in AccuWeather's proprietary forecasting engine. AccuWeather reports 3x faster dataset development (three months to one month per dataset), a 50% reduction in unactionable alerts, and 50% cost savings on serverless job usage.
AccuWeatherLakeflow Jobs · Delta Sharing · DatadogAdobe brings creativity to life with Databricks
Adobe uses the Databricks Data + AI Platform for end-to-end data management that unifies all data and AI at scale, with 20% faster performance. Databricks equips over 92 teams at Adobe to unify data from financials, sales, products, customers and employees so they can drive personalized experiences across Adobe's digital platforms with AI.
Was this helpful?
Your feedback helps us improve our use case database