In this session, we will discuss the strategies and thought process one should adopt for modeling and partition data effectively in Azure Cosmos DB. We will also briefly cover related topics such implementing optimistic concurrency control, transactions with stored procedures, batch operations, and tuning queries + indexing
Database Partitioning has been around for a while but is always being updated and enhanced. In today big data volume world, we to think how we are going to support these large tables.
Azure Stream Analytics is a fully managed serverless offering that enables customers to perform real-time data transforms and hot-path analytics using a simple SQL language. In this session, we will show how to combine SQL reference data to augment data coming from devices and create real-time alerts, leverage partitioning to write data to SQL at high speed, and create real-time dashboards.
Azure Cosmos DB has many use-cases, and not all of them are clear to Azure Cosmos DB newcomers. If you're a relational expert and have been wondering about graph, how you'd survive without a schema, and scale out databases this session can help.