Azure Cosmos DB is the industry's first globally distributed multi-model database service. Features of Cosmos DB include turn-key global distribution, elastic throughput and storage, multiple consistency models, and financially backed SLAs. As well, we are in preview for Table, Graph, and Spark Connector to Cosmos DB. Also includes healthcare scenarios!
20. Key benefits
• Cosmos DB supports fast ingestion
of message data from 1:1
communication, group chats
• Cosmos DB enables real-time query
over message and group
conversations, with custom filters on
when user enters/leaves thread
Business need
• Provide search capabilities over
TBs-PBs of Skype and Teams
conversations
• Fast ingestion with multiple
writes, overlay group
memberships
• Secure & compliant data storage
with high privacy requirements
Azure Cosmos DB
Azure Cosmos DB
Azure Cosmos DB
USERS
GROUPS
MESSAGES
Skype Ingestion
service
Skype Query
service
44TB
Message data
Skype powers 1M searches per
second over conversation data
6TB
User data
1TB
Group data
21. Key benefits
• Cosmos DB can scale elastically
without operational overhead of
MongoDB
• Perform fast queries over events to
deliver recommended services,
safety notices to vehicles
• Perform staged migration via
MongoDB APIs
Business need
• Need to ingest massive
volumes of diagnostic data
from vehicles and take real-
time actions as part of
connected car platform
• Management and operations
of database infrastructure to
handle exponential growth of
data
8TB
Vehicle Telemetry
250K
Lexus Cars
Toyota drives connected car push
forward with Azure Cosmos DB
Azure Cosmos DBAzure HDInsight
Storm
Azure Storage
(archival)
22. Business need
• Process Ms of retail transactions
per second in milliseconds in
inventory pipeline during peak
(“Black Friday”)
• Fast development cycles and
loosely coupled micro-services to
keep up with a competitive
marketplace
Key benefits
• Cosmos DB provides elastic
scalability from 1-10M requests per
second
• Improved reliability, and faster order
processing times than previous OSS
solution
• Reduced development time and
operational overhead
Azure Cosmos DB
Azure Service
Fabric
Pricing Service
Azure Cosmos DB
Azure Service
Fabric
Inventory Service
E-commerce challenger eyes the top spot,
runs on Azure Cosmos DB
12TB
Provisioned
10M
Peak RPS
64
Databases
23. Business need
• Handle millions of players on
Day 1 due to popularity of the
TV series
• Match-making of players for
competitive and lag-free
experience
• Provide new content weekly,
and iterate on social
functionality
•
Key benefits
• Cosmos DB provides elastic
scalability for millions of users and
flexible schema to support social
features and gameplay
• Global distribution allows for low
latency for players spread
worldwide
• Automatic indexing used to build
real-time leaderboards
Performance at massive scale allows
millions to play mobile game
Azure Traffic
Manager
Azure API Aps
(game backend)
Azure CDN
Azure Cosmos DB
Azure Functions
Azure Notification
Hubs (push
notifications)
Azure Storage
(game files)
1M
Peak Active
#1
iOS App Store
1B
Daily Queries
25. Global distribution Elastic scale out Guaranteed low latency Comprehensive SLAs
Azure Cosmos DB
Key-Value Column-family GraphDocuments
A globally-distributed, multi-model database service
… more coming soon
Five consistency models
SQL
26. Thank you!
Status updates – Follow us @AzureCosmosDB or #CosmosDB
Support – Email AskCosmosDB@Microsoft.com
42. Bed Sensors | OR Scheduling | Precision Medicine
Healthcare Scenarios
43. Bed Sensors Scenario
Classic Internet of Things (IoT) Scenario – large
stream of data from disparate sources (e.g.
connected car scenario).
Cosmos DB is well suited as it is a write-optimized
database engine with SLAs for latency, consistency,
throughput, and availability
Build models to interact with data at change feed or
build Spark Streaming continuous application in front
Models able to decipher what information is important
and when to alert
44. Bed Sensor Scenario
respiratory rate,
bed movement,
heart rate, etc.
Use Spark Streaming to filter
and extract important data
Store FHIR / json data
Change feed contains all
the changes so
downstream alerting and
ML algorithms can quickly
act on patient vitals
Actions: e.g. turn
patient to prevent
pressure ulcers due
to lack of body
movement for x
hours.
Patient Care
Cosmos DB
Data Sciences
45. Operating Room Scheduling
Efficiency dependent on staffing and allocation, not
workload (cases)
Lack of OR availability means loss of patients
Better utilization = better profit margins, reduced
support, and maintenance costs
Better medical staff efficiencies = better outcomes
Shorter waiting times and less cancellations
46. Image Source: Anesthesia & Analgesia,
December 2006, Volume 103, Issue 6
“You are not going to get the elephant to shrink or change its size. You
need to face the fact that the elephant is 8 OR tall and 11hr wide”
Steven Shafer, MD
47. Events | Alerts Cosmos DB Change Feed
ML algorithms to predict
scheduling available
Auto-rescheduling based
on triggers or ML algo
Notify / alert for resources
Actions via ML and Triggers
Cosmos DB: Change Feed, Data Sciences
48. Precision Medicine: FHIR + Genomics
HL7 FHIR is JSON data, well suited for Cosmos DB
Notifying patients of HL7 FHIR health care record
changes using Logic Apps and Azure Cosmos DB
Combine FHIR data with genomics with Data
Sciences (Machine Learning, Deep Learning, AI, etc.)
Developer Personalized Medicine solutions
+