Azure Cosmos DB Use Cases

1. Azure Cosmos DB Use Cases 2019

2. Managing and syncing data distributed around the globe Modern apps face new challenges Delivering highly-responsive, real-time personalization Processing and analyzing large, complex data Scaling both throughput and storage based on global demand Offering low-latency to global users Modernizing existing apps and data

3. Azure Cosmos DB Core (SQL) API Table API MongoDB Graph Document Column-family Key-value Guaranteed low latency at the 99th percentile Elastic scale out of storage & throughput Five well-defined consistency models Turnkey global distribution Comprehensive SLAs

4. Azure COSMOS DB Use Cases NoSQL modernization and migration to Azure Cosmos DB Modernize and build new apps with real-time personalization 99.999 HA for reads and writes, extremely low latency at any scale worldwide Deliver high-quality App experiences globally at any scale • Multi-Player games • Social Clans / Guilds, Leaderboards and Messaging Handle peak sales periods with ease • Retail and e-commerce Apps • Modern apps that need to elastically scale to handle spikes in traffic Deliver relevant real-time personalization • Any modern customer facing application Leverage IoT telemetry to build differentiated experiences • Manage Device telemetry • Device Registry Top sectors including Retail, IOT/ Manufacturing, Gaming, and ISV; emerging sectors include Financial Services and Health Care.

5. Azure Cosmos Industry Scenarios • Retail • Order Processing Pipeline • Product Catalog • Personalization • Real-time analytics • Financial Services • Audit Trail • Tax Forms • Risk Analysis • IoT + Manufacturing • Device Telemetry • Device Registry • Supply Chain Management • ISV • Content Management (CMS) • Data Interchange • Dev Ops Dependency Management • Knowledge Graphs • Gaming • Social Clans/Guilds • Leaderboards • Messaging • Healthcare • Data Interchange (HL7 FHIR)

6. NoSQL modernization and migration to Azure Cosmos DB

7. Easy to MIGRATE nosql apps to Azure Cosmos DB Make data modernization easy with seamless migration of NoSQL workloads to cloud. • Azure Cosmos DB MongoDB API, Cassandra API, and SQL API bring app data from existing NoSQL deployments • Leverage existing tools, drivers, and libraries, and continue using existing apps’ current SDKs • Turnkey geo-replication • No infrastructure or VM management required MongoDB Cassandra NoSQL wire protocol DynamoDB Azure Cosmos DB: MongoDB APICassandra APISQL API Couchbase Neo4j HBase CouchDB

8. Migrate Cassandra/DataStax workloads to Azure Cosmos DB Top reasons for customers to migrate to Azure Cosmos DB • Competitive TCO - Up to 2- 6X in saving when moving from On-Premise/IaaS Cassandra to Cosmos DB • Offers a fully managed service - reduces the need to manage and configure the database • Cosmos DB guarantees high performance anywhere in the world - with industry leading SLAs for high availability and low latency Questions to ask customers with Cassandra workloads • Does the database have high costs of infrastructure, licenses and database management • How much time is spent managing the database vs focusing on innovation? It is hard to manage and configure Cassandra database is hard and time-consuming including: • Capacity Management, • Performance Management • Availability Management • Are you trying to achieve Global scale ? – Building high performing scalable apps across multiple regions is difficult and time consuming Target Audience: • ITDM • Head of development • Architects • High Potential Industries: • Retail • Manufacturing (IOT scenarios) • Automotive • Financial Services • Gaming • Top resources to support you with this scenario • NoSQL Migration to Azure SafePassage Program • NoSQL to DB Migration Guide • NoSQL Migration FAQ • Cosmos DB SI Partner List • FY19 NoSQL Migration Offer • Cosmos DB Infopedia Page 3rd Party Tools & Services to support Migration • Inmanis Data • Striim Successful Customers

9. Migrating Cassandra Workloads • What was the app they migrated? • SPOC is a notification service for Symantec endpoints. • Every Symantec products (SEP, Norton security product’s) endpoint will register with SPOC and they open a constant long poll to the SPOC server. • For every write done SPOC, there will be a subset of reads happening from clients based on channel. • Whenever there are new changes/updates come to SPOC, they are propagated to all connected eligible devices. Symantec is migrating multiple workloads from DSE Cassandra. Leveraging multiple APIs depending on the workload requirements Chose Azure Cosmos DB because it offers fully managed service, reduces pain of managing and scaling the database and SLAs around high availability and low latency.

10. Migrating from Mongo DB • Current challenges that while using Mongo DB on a VM • Ingesting and managing different data from multiple sources with multiple models • Manageability and scalability became a major DevOps concern • Trying to data can be ingested from several products and then consolidated into a single persistent storage was time consuming and challenging. Bentley is an ISV with several cloud services for manufacturing organizations. As part of this they need to ingest construction data from several products and then consolidated into a single persistent storage. They turned to Azure Cosmos DB for its fully managed and globally scalable service and its compatibility with MongoDB. case study here • Why they migrated to Azure Cosmos DB • A highly performant and globally scalable database service • Fully manage service allow Bentley to be more agile and reduced need for data management • Azure Cosmos DB offers a dynamic schema which allowed Bentley to ingest data from multiple sources and creating maps between the various schemas in it. ‘Building a flexible, scalable data layer with Azure Cosmos DB will enable us to deliver actionable insights to our users.” says Phil Christensen, Senior Vice President for Reality Modeling & Cloud Services at Bentley Systems. View the case study here

11. Retail

12. Handle peak sales periods with ease Azure CDN Azure Storage (files) Offer customers fast and reliable service quality during seasonal and other high-traffic sales periods. Instant, elastic scaling handles traffic and sales bursts Provisioned throughput ensures predictable performance for mission critical microservices (e.g. shopping cart) Low-latency data access from anywhere in the world for fast, robust user experiences High availability across multiple data centers Azure API Apps (backend) Azure Cosmos DB (database) Apache Spark (analytics) Azure Functions Azure Notification Hub (Push notifications) Walmart Labs (aka jet.com) ensures reliable app experience for customers on Black Friday, Cyber Monday, and other high traffic periods

13. Product catalog Reference architecture

14. Order processing Reference architecture

15. Order processing Reference architecture https://aka.ms/order-processing

16. Deliver relevant Real-Time recommendations Online Recommendations Service HOT path Azure Service Fabric (Personalization Decision Engine) Azure Cosmos DB (distributed model store) Help customers discover items they’ll love with real-time personalization and product recommendations. Machine learning models generate real-time recommendations across product catalogues High volumes of product data can be analyzed in milliseconds Low-latency ensures high app performance worldwide Tunable data consistency models for rapid insight Azure Data Factory (scheduled job to refresh persisted models) .com (Product Details Page) Shoppers Azure Event Hub Azure Data Lake Storage (offline raw data) Apache Spark Offline Recommendations EngineCOLD path ASOS deliver personalized shopping experiences and real-time order updates to 15 Million customers. Helping them grow and win with millennial shoppers.

17. Recommendation Engine Reference architecture https://aka.ms/recommendation-engine

18. Real-time analytics Reference architecture https://aka.ms/retail-analytics

19. IoT + Manufacturing

20. Leverage IoT telemetry to build differentiated experiences Diverse and unpredictable IoT sensor workloads require a responsive data platform • Real-time vehicle diagnostics • Instant elastic scaling • No loss in ingestion or query performance Azure IoT Hub Apache Storm on Azure HDInsight Azure Cosmos DB (Telemetry & device state) Azure Web Jobs (Change feed processor) Azure Storage (archival) Logic apps Azure Cosmos DB was chosen due to its ability to ingest data at massive scale with high availability (99.99%) guarantee.

21. Stream Processing Reference architecture https://aka.ms/stream-processing-databricks

22. Stream Processing Reference architecture https://aka.ms/stream-processing-sa

23. IoT, Big Data optimize operations at ExxonMobil subsidiary Find a better way to monitor remote wells and collect data on performance • Must be cost efficient • Unified device management and streaming • Automate IOT and analytics • We had a team of five people working on this, and they built it from scratch. The ease of use of the Azure services and the support we got from Microsoft made that possible. .

24. Stream Processing Reference architecture

25. Stream Processing Reference architecture https://aka.ms/streaming-scale-cosmosdb

26. Gaming

27. Deliver High-Quality Experiences At Any Scale Globally  Azure CDN Azure Storage (files) Need a database that seamlessly responds to massive scale and performance demands • Multi-player game play with low latency • Instant capacity scaling from launch onward • Uninterrupted global user experience Azure API Apps (backend) Azure Cosmos DB (database) Apache Spark (analytics) Azure Functions Azure Notification Hub (Push notifications) The Walking Dead: No Man’s Land chose Azure Cosmos DB because of its extremely low latency and massive scale worldwide.

28. Leaderboards Reference architecture https://aka.ms/azure-gaming

29. Game Analytics Reference architecture https://aka.ms/azure-gaming

30. Financial Services

31. Fidelity build Mortgage Insurance App to enhance customer experience • Fidelity built a new application – EXOS – it is the only mobile digital mortgage application designed specifically to extend and enhance every critical consumer touchpoint throughout the entire mortgage lending life cycle. • EXOS offers a real-time personalized experience for customers across the entire mortgage process including • Appointment scheduling and communications – enhancing customer experience and process . • Ensuring consistent , personalized and accurate information for customer throughout the process. • EXOS Closing offers unmatched consumer satisfaction and transparency in to the closing process. Fidelity chose Azure Cosmos DB due to the Ease global distribution, ability to scale and fully managed service reducing the database management overhead.

32. a financial trend saas engine for investors Need a database that can handle any schema and adapt quickly to rapid changes • Financial SAAS engine with no dev ops • Super fast to handle financial data • Scalable on demand, globally distributed • Business models are under attack, especially in the financial industry. Azure Cosmos DB is a technology that can adapt, evolve, and allow a business to innovate faster in order to turn opportunities into strategic advantages.

33. Real-time payments pipeline Steady state - 10M transactions/day, peak hours - 3-4K transactions/sec • Financial SAAS engine with no dev ops • Super fast to handle financial data • Scalable on demand, globally distributed • Centralize payment pipelines, build real time processing, analytics. Goal to introduce a common pipeline accepting transactions from all different sources and distributing them to the right pipeline and also other sources like analytics.​

34. Securities processing Reference architecture

35. Image classification Reference architecture https://aka.ms/image-processing

36. ISV

37. maps out successful strategy with CosmosDB World’s third largest mapping agency • Support for spatial queries and standards. • Identify every roof top in Britain. • Scalability and flexibility to handle millions of properties. • The solution can identify roof types of all 35.7 million properties in Britain in less than 24 hours with 95% accuracy.

38. Migration from Mongo DB • Current challenges that while using Mongo DB on a VM • Ingesting and managing different data from multiple sources with multiple models • Manageability and scalability became a major DevOps concern • Trying to data can be ingested from several products and then consolidated into a single persistent storage was time consuming and challenging. Bentley is an ISV with several cloud services for manufacturing organizations. As part of this they need to ingest construction data from several products and then consolidated into a single persistent storage. They turned to Azure Cosmos DB for its fully managed and globally scalable service and its compatibility with MongoDB. case study here • Why they migrated to Azure Cosmos DB • A highly performant and globally scalable database service • Fully manage service allow Bentley to be more agile and reduced need for data management • Azure Cosmos DB offers a dynamic schema which allowed Bentley to ingest data from multiple sources and creating maps between the various schemas in it. ‘Building a flexible, scalable data layer with Azure Cosmos DB will enable us to deliver actionable insights to our users.” says Phil Christensen, Senior Vice President for Reality Modeling & Cloud Services at Bentley Systems. View the case study here

39. Migration from Cassandra • What was the app they migrated? • SPOC is a notification service for Symantec endpoints. • Every Symantec products (SEP, Norton security product’s) endpoint will register with SPOC and they open a constant long poll to the SPOC server. • For every write done SPOC, there will be a subset of reads happening from clients based on channel. • Whenever there are new changes/updates come to SPOC, they are propagated to all connected eligible devices. Symantec is migrating multiple workloads from DSE Cassandra. leverage multiple APIs depending on the workload requirements Chose Azure Cosmos DB because it offers fully managed service, reduces pain of managing and scaling the database and SLAs around high availability and low latency.

41. Appendix

42. Summary of top performing Industry Use Cases To be updated !

43. Resources • Solutions Architectures • ASOS case study (retail, real-time personalization) • Next Games case study (gaming, elastic scaling) • Johnson Controls story (IoT)