Real-Time Analytics for Logistics
Track and analyze data points across your fleet, the environment and inventory management system to make real-time decisions
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Logistics
Monitoring and tracking is critical to ensuring your fleet is operational, routes are optimized and resources are delivered on-time and within budget. The surge in online ordering and the expectation of short delivery timeframes has made real-time optimizations a must in the industry. With Rockset, you can analyze thousands of data points across multiple sources to respond to changing conditions and identify problems early on.
Logistics Use Cases
Fleet Management
Manage and monitor the health of your fleet with real-time visibility into vehicle locations and conditions. Get alerted to changes in the health of your vehicles so that you can schedule preventive maintenance and keep your fleet running.
Construction
Operate “just in time” by sequencing the arrival of materials to the site. Keep your site safe, organized and your construction project under budget with real-time monitoring.
Delivery Services
Optimize delivery routes and improve efficiency with real-time data from GPS devices, orders and delivery schedules. Let your customers track their deliveries in real-time to enable a smooth ordering and delivery process.
Why Rockset
Why Real-Time Analytics in Logistics Is Hard
How Rockset Makes It Easy
Need to analyze real-time data at scale: Route optimization and changes to the supply chain are made from real-time data streaming from thousands of devices and machines. The analytics infrastructure should handle high ingest rates and make that data queryable in seconds.
Act on streaming data in real-time: Rockset ingests data continuously and makes it immediately queryable without any data prep. Rockset’s disaggregated architecture separates ingest compute from query compute so you can scale to handle peak periods.
Can’t gather information across various sources: Decisions cannot be made in a vacuum. Logistics systems rely on data from multiple sources including GPS, weather, fleet management and inventory management systems.
Join data across multiple sources: Join data from different sources and formats using SQL. Optimize your supply chain, distribution and fleet management based on constantly changing data from multiple sources.
Need to know your queries upfront: You need to drill-down and analyze the root cause of issues in your supply chain. Many systems require the access patterns of the application to be defined upfront, making it challenging to run ad-hoc analysis of the data.
Analyze data on the fly: Rockset doesn't require data to be modeled a certain way for queries to perform well. Rockset indexes your data in real-time to support low latency search and analytics without any additional data modeling.
Why Real-Time Analytics in Logistics Is Hard
Need to analyze real-time data at scale: Route optimization and changes to the supply chain are made from real-time data streaming from thousands of devices and machines. The analytics infrastructure should handle high ingest rates and make that data queryable in seconds.
Can’t gather information across various sources: Decisions cannot be made in a vacuum. Logistics systems rely on data from multiple sources including GPS, weather, fleet management and inventory management systems.
Need to know your queries upfront: You need to drill-down and analyze the root cause of issues in your supply chain. Many systems require the access patterns of the application to be defined upfront, making it challenging to run ad-hoc analysis of the data.
How Rockset Makes It Easy
Act on streaming data in real-time: Rockset ingests data continuously and makes it immediately queryable without any data prep. Rockset’s disaggregated architecture separates ingest compute from query compute so you can scale to handle peak periods.
Join data across multiple sources: Join data from different sources and formats using SQL. Optimize your supply chain, distribution and fleet management based on constantly changing data from multiple sources.
Analyze data on the fly: Rockset doesn't require data to be modeled a certain way for queries to perform well. Rockset indexes your data in real-time to support low latency search and analytics without any additional data modeling.
Core Features
Built-In Data Connectors
Set up continuous ingestion from common data sources, like MongoDB, DynamoDB, Kafka and S3, in a plug-and-play manner. New data is reflected in Rockset in seconds.
SQL with JOINs
Join multiple data sets for analysis. Rockset supports full-featured SQL, enabling complex search, aggregation and join queries.
Converged Index™
Rockset automatically builds search, columnar and row indexes on your data to deliver fast queries at scale.
Serverless Autoscaling
Rockset scales storage, ingest and query layers automatically and independently in response to growth and spikes in usage.
Resources
Related BlogWhere's My Tesla? Creating a Data API Using Kafka, Rockset and Postman to Find Out
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Customers
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