Introduction to Cosmos DB (TH18) - Las Vegas 2019

Leonard Lobel

This session presents an overview of Azure Cosmos DB, a globally distributed, massively scalable, low (single-digit millisecond) latency, fully managed NoSQL database service that is designed specifically for modern web and mobile applications. Like other NoSQL platforms, Cosmos DB supports a schema-free data model, built-in partitioning for sustained heavy-write ingestion, and replication for high availability. But only Cosmos DB offers turnkey global distribution, automatic indexing, and SLAs for guarantees on 99.99% availability, throughput, latency, and consistency.

We begin by explaining NoSQL databases in general, and how they compare with traditional relational database platforms. Then we tour the many features of Cosmos DB, including its multi-model capabilities which allow you to store and query schema-free JSON documents (using either SQL or MongoDB APIs), graphs (Gremlin API), and key/value entities (table API). You'll learn about global distribution, scale-out partitioning, tunable consistency, custom indexing, and more. We'll also discuss client development using the many available SDKs. Attend this session, and get up to speed on Cosmos DB today!

You will learn:

  • About NoSQL databases, and Microsoft Azure Cosmos DB
  • The differences between NoSQL and relational database platforms, and when to choose one or the other for your next application
  • About the unique NoSQL features of Cosmos DB, including global distribution, server-side horizontal partitioning, multi-model support, rich query over schema-free data, client development, server-side programming, tunable consistency, and automatic indexing

Introduction to Cosmos DB (TH18) - Las Vegas 2019

  • $25.00

Tags: AI, Data and Machine Learning, Azure Cosmos DB, NoSQL database, global distribution, server-side horizontal partitioning, multi-model support, rich query over schema-free data, client development, server-side programming, tunable consistency, automatic indexing

Categories: AI, Data and Machine Learning Las Vegas Leonard Lobel