Azure Cosmos DB Conf

On Demand Sessions

Blowing your mind with F#

F# is the lesser known of the .NET programming languages, but it can pack a punch when it comes to building applications. But what does that have to do with CosmosDB? What if I told you that you could get compile time checking of the validity of your database access, the collections to query and the queries themselves? I'd say that you'll have to join me and find out!

Aaron Powell

Partitioning Tips for Cosmos DB to Increase Performance and Save Money

Choosing the right partition key in Cosmos DB is complicated, but the right key will help you both increase the performance of your application and reduce the number of RUs you need to provision. There are several things to consider when picking a good key including how evenly it spreads both the physical layout of your data and the volume of requests across all partitions. In this session we will walk through a list of questions to ask yourself when picking a good key and we will explore a few real world customer scenarios.

Justine Cocchi

Real World NoSQL design patterns with Azure Cosmos DB

In this session we will go over several real world NoSQL design and solution patterns to illustrate how CosmosDB is used to help customers to solve critical business challenges and focus on best practices of building distributed scalable and resilient systems.

Sergiy Smyrnov

A deep-dive into the Cosmos DB repository-pattern .NET SDK

A code-heavy presentation introducing the Cosmos DB repository-pattern .NET SDK from the author of the library. In this presentation, David Pine of Microsoft, will demonstrate the inner-workings of the repository-pattern .NET SDK that wraps the official Azure Cosmos DB .NET SDK, simplifying the consumption of the service offering. The SDK boasts: - Configuration to optimize bandwidth - Optional container per item type - Bulk execution - Async APIs - Advanced partitioning strategy - Simple & elegant IRepository interface https://github.com/IEvangelist/azure-cosmos-dotnet-repository

David Pine

From the trenches: Building an awesome multitenant SaaS with Cosmos DB and Azure

A real-world case study of how Whally, a multitenant SaaS startup, built a modern platform from scratch on Cosmos DB and Azure. Noah shows the design and implementation decisions he made related to partitioning, data modeling, secure multitenancy, performance, real-time streaming from change feed to SignalR and more, all using ASP.NET Core on Azure App Services. This session aims to go beyond the docs to show a real example of how Cosmos DB is powering apps in the wild.

Noah Stahl

Explore Graph Analytical use-case with Azure Cosmos Gremlin API and Azure Synapse Spark graphframes

In this session you will get introduced to Azure Cosmos Gremlin API, Azure Synapse Link, Spark and learn Cosmos Gremlin API best practices as well as how to use combination of these technologies to explore your Graph data for common Graph Analytical use-cases using Spark graphframes library.

Sergiy Smyrnov

Integrating Cosmos DB with Azure Functions

A session that explains how to use the input and output bindings and Cosmos DB Triggers within an Azure Function Application using C#.

Gabriela Martínez

How does Azure Cosmos DB work under the hood?

To master any technology, you need to understand the foundation of how it works on the back-end first. In this session; We will explore Azure Cosmos DB's infrastructure. I will explain you how Azure Cosmos DB works and handles data in the back-end. We will cover the basics and some of the most misunderstood features of Azure Cosmos DB. Learning new technologies make you a better leader and collaborator. Join me to learn more about this new Cloud Database technology.

Hasan Savran

Implementing an Event Sourcing strategy on Azure

In recent years the Event Sourcing pattern has become increasingly popular. By storing a history of events it enables us to decouple the storage of data from the implementation of the logic around it. And we can rebuild the state of our data to any point in time, giving us a wide range of opportunities around auditing and compensation. In this demo-heavy session you will learn how we can use Azure Event Hubs to process and store these events to build our own event store based on Cosmos DB. Moreover, we will also dive into options around connecting to other Azure services and even Kafka applications to easily implement this popular pattern in our own solutions.

Eldert Grootenboer

Olena Borzenko-Turianska

Optimizing Request Unit Consumption

Cosmos Db is a "Database as a Service" product, where we don't have control of hardware configuration but instead use "request units" to specify the resources of our database. Nonetheless, this doesn't mean that there is nothing to do on the performance side, and there are specific ways to get more out of our request units and deliver our data even faster. From consistency, indexing, connectivity settings, global replication, we will cover everything that can have an impact on your throughput and latency. In this demo-heavy session we will go into the request units concept and look at how all these different settings impact consumption and cause an increase or decrease of query and data modification throughput.

Warner Chaves

Cosmos DB for everyone using Graphistry' no-code and low-code GPU visual graph analytics

From security and fraud to sales and marketing, teams are adopting graph analytics to understand the relationships across their data. CosmosDB solves how to execute Gremlin graph queries, which is great for software.  However, for people in an organization to also successfully harness graph reasoning by exploring and interacting with their data, they also need tools. We share how to bridge those gaps by combining CosmosDB with Graphistry. Whether it's a business analyst needing a customer 360, an investigator scoping an incident, a data scientist iterating on a model, or a developer building solutions, we'll share examples of how to quickly explore their CosmosDB data and create point-and-click graph solutions. Importantly, we show how to specialize the interaction style to their preference on coding vs point-and-click. Our talk focuses on three emerging capabilities in visual graph computing for enabling CosmosDB analysts: No-code visual graph analysis for everyone, low-coding specialized for analysts vs researchers vs engineers, and scaling visual insights with GPUs. We'll use examples from our enterprise and federal uses such as on identity data, logs, ML, and social media.

Leo Meyerovich

Access Azure Cosmos DB with Entity Framework Core

EF Core is the data access API of choice for .NET developers. Although considered by most to be an object relational mapper (ORM), the team recently added support for the Azure Cosmos DB SQL API. Learn how EF Core simplifies building Cosmos DB apps with hands-on demos, explore the pros and cons of using EF Core and receive the tools and tips that will help you decide whether EF Core is the right solution for your needs.

Jeremy Likness

Architecting Cloud Native Apps with AKS and Cosmos DB

In this session will look at modern app development and how using Kubernetes (in this case AKS) presents a number of advantages, couple this with a native Azure service like Cosmos DB can be a winning combination. We will examine running databases in containers such as Mongo DB and we will also discuss how Kubernetes and Cosmos DB can compliment each other to provide an enterprise grade solution.

Ben Griffin

Visualizing Cosmos DB Graph Data Over Time and Space

When building an application that takes advantage of graph data, selecting the data source and getting the data model right is seen as the entire solution but it is often only the first step. You then need to figure out how to present that data back to end users in a way that actually helps them make decisions that solve problems. In this session, Corey will discuss solutions and designs for traditional node-link diagrams using libraries from Cosmos partner Cambridge Intelligence, and will also show strategies for communicating temporal patterns in graphs using Cambridge Intelligence's new product, KronoGraph.

Corey Lanum

Migrating to Cosmos DB's API for MongoDB

Azure Cosmos DB's API for MongoDB is Microsoft’s implementation of the wire protocol for MongoDB built on top of the foundational Azure Cosmos DB engine. This session will be focused on migration to Cosmos DB's API for MongoDB from on-premises or cloud instances of MongoDB using native MongoDB utilities such as mongodump as well as Database Migration Service. We will be talking about the advantages, pre-requisites and considerations for both the methods while walking through a demo of the migration for a MEAN stack application.

Shweta Nayak

Experiences from 7 years of Cosmos DB

Cosmos DB is a powerful tool. It may look simple on the cover, since "it just works", but the performance and cost optimizations are rarely simple. This presentation looks at Cosmos DB from a few different viewpoints. We look at experiences gained from some real-world cases and stories, from mistakes made and successful optimizations done. At the end, we draw a couple of best practices from these experiences. This presentation is aimed for developers / data engineers, and can at times be on advanced level, although for the most part the talk will be aimed at intermediate audience.

Sakari Nahi

Real Life migration from PostgreSQL to Cosmos DB

Follow us in the migration process of an existing customer application working on PostgreSQL to Cosmos DB. We will show you step by step the different iterations of the project, from the initial discovery of the relational data model to the optimization of the application to work efficiently with Cosmos DB.

Julien Michel

Rumen Krastev

Search and Explore your Cosmos DB data with Azure Cognitive Search

Organizations what to make full use of their data and often this means being able to gain more insights, explore and search this data. In this session, we will explain how Azure Cognitive Search, an AI enabled PAAS search service, can be integrated with Cosmos DB to not only extract critical knowledge from this data, but then enable users to search, find answer to questions and extract deep insights found within this data.

Liam Cavanagh