DocumentDB is a fast, globally distributed, multi-model NoSQL database service. It provides automatic scaling of storage and throughput, high availability across regions, flexible data models, and developer productivity with support for SQL and JavaScript queries. Customers can use DocumentDB for building scalable applications that need to handle large volumes of data across any number of regions worldwide with low latency and high availability.

1. DocumentDB: Blazing fast planet-scale NoSQL
DocumentDB Team
E-mail: askdocdb@microsoft.com
Twitter: @documentdb

2. The NoSQL landscape
2

3. NoSQL Evolution
Volume
Velocity
Variety
• How can my app deal with massive
volumes of data and throughput?
• How do I elastically scale my database?
• How do I write responsive apps?
• How do I make data available where my users are?
• How do I write highly available apps?
• How do I deal with schema changes?
• How do I iterate rapidly?
• What data models work at scale?

4. NoSQL Evolution
Volume
Hyper
converged/hyper
scale architectures
Horizontal
partitioning
Elastic scale
Velocity
Write optimized
database engines
Global distribution
Active-active
topologies
Tunable
consistency
Variety
Dynamically typed
databases
Schema Free
databases
Logical index
layouts (inverted,
columnar etc)
2009
MongoDB/
Riak/Neo4J
2015
DocumentDB
GA
2006
BigTablep
aper
Cassandra
20082007
Dynamo paper/
AWS SimpleDB
2014
DocumentDB
Preview
20162012
AWS DynamoDB
2010
Project
Florence

5. Onesizedoesnotfitall
Azure PaaS
Scale-up
Co-located compute & storage
Index Mgmt
/QP
Local
persistence
Local
compute
& storage
• A single database
up to 1TB (future,
4TB)
Azure SQL DB
Read optimized
Relational
Scale-Out
Disaggregated remote storage
Distributed file system
<1 EB
Azure Data Lake/U-SQL, HDInsight/Spark
Data Lakes
Compute runtimes
…
Index Mgmt
/QP
Local
persistence
Local compute &
storage on each
shard
Scale-out
Co-located compute & storage
• A single collection 1PB &
100s of millions of req/sec
• Multiple collections in a
database
Azure DocumentDB
Write and Read optimized
NoSQL

6. Common scenarios
Retail, CMS, Education
• Product Catalog
• Product Recommendations
• Personalization
• Campaign Management
• Blogs and CMS
Gaming
• Multiplayer Games
• Social Gameplay
• Leaderboards
• Game analytics
IoT, Sensor Data
• Telemetry + Event Store
• Telematics
• Device Registry
Social Analytics, Ad Tech
• User behavior telemetry
• Personalization
• Customer 360 view

7. Capabilities

8. Globaldistributionfromthe
ground-up

9. Regional Availability
As a Ring 0 service, DocumentDB will be available by default in all new Azure regions

10. Guaranteed Low
Latency
“I want my data wherever my users are.”
Reads <10ms @ P99, <1ms @ P50
Writes <15ms @ P99, <6ms at P50
• Globally distributed with reads and
writes served from local region
• Write optimized, latch-free database
engine designed for SSDs and low
latency access
• Synchronous and automatic indexing
at sustained ingestion rates

11. GuaranteedLowLatency
11

12. Elastically scalable storage
• System designed to independently scale
storage and throughput
• Transparent server side partition
management and routing
• Automatically indexed SSD storage
• Automatic global distribution of data
across any number of Azure regions
• Optionally evict old data using built-in
support for TTL

13. Elastically scalable
throughput
• Elastically scale throughput from 100 to
10s of millions of requests/sec across
multiple regions.
• Customers pay by the hour for the
provisioned throughput.
• Transparent server side partition
management and routing.
More throughput
Less throughput
9PM PST
Less throughput
More throughput11PM PST

14. 99.99% availability SLA
• Multi-homing APIs - apps don’t need to
be redeployed during regional failover
• Customers can simulate/trigger manual
failover (via portal or APIs)
• Automatic failover (policy driven) in the
event of regional failures
• All clusters configured with 10-20 FDS
• Each partition is protected by a replica set
• Majority quorum based durable,
synchronous commits within a DC
99.99%

15. Highavailability
15

16. Well defined
consistency models
• Global distribution forces us to
navigate the CAP theorem
• Intuitive programming model for well-
defined, relaxed consistency models
with clear PACELC tradeoffs
• Four well-defined consistency levels
to choose from
• Can be overridden on a per request
basis
Strong consistency,
High latency
Eventual consistency,
Low latency
27%
3%
54%
16%
Observed Distribution
BoundedStaleness
Eventual
Session
Strong

17. Schema agnostic indexing
• At global scale, ALTER TABLE and schema/index management
is a non-starter
• Automatic and synchronous indexing of all ingested content
• No need to define schemas or secondary indices upfront!
• Highly write optimized database engine with latch free and log
structured techniques
• Fully resource governed with back pressure and rate limiting
built into the log structured storage engine
• Online and in-situ index transformations
No Problem
No Schema

18. Rich SQL and JavaScript queries
• No impedance mismatch - JavaScript is the
type system of the database engine
• Query using either SQL and JavaScript (or
both)
• Write business logic entirely in JavaScript
with stored procedures and triggers
• JavaScript language integrated multi-item
ACID transactions with snapshot isolation

19. TCP (SSL), HTTPS
DocumentDB Database Engine
AccessingDocumentDB
SQL JavaScript MongoDB
Query IL Database Runtime
Java .NET
Native DocumentDB client drivers
Java
.NET
Ruby
…
Native MongoDB client drivers
…
…
…

20. Roadmap
• Unique Index
• Aggregates
• Deeper engine level integration
• Support for more databases
Customer Growth
• Significant customer growth since the initial
launch
• ISVs : Parse, Sitecore and others
• Large MongoDB customers running into
security, scalability, robustness issues with
MongoDB
MongoDBAPICompatibility
Core database operations CRUD/Query
• Insert, InsertMany, InsertOne, Update, UpdateMany, UpdateOne, ReplaceOne, DeleteOne,
DeleteMany, Remove
• $inc, $mul, $rename, $set, $unset, $min, $max
• $addToSet, $pullAll, $pull, $pushAll, $slice, $push, $pop, $each, $sort, $position, $all, $size,
$elemMatch
• Bitwise, comparison, logical operators
• $type,
• $mod, $regex,
• $2dspehere, 2d, polygon, $near, $nearSphere, $geoWithin, $geoIntersects (incl. geometry
support for points, lines, polygons sphere)
• find, insert, update, delete, getLastError, getMore, findAndModify
• getnonce, logout, authenticate
• createIndex, listIndexes, dropIndexes, connectionStatus, reIndex, listDatabases, collStats,
dbStats
Turnkey
• Fully managed, fully secure and compliant and backed by SLAs for availability, latency,
consistency and throughput
• Partitioned collections
• Global distribution across any number of regions

21. Security and Compliance

22. Security

23. Compliance
Certification Details Compliance Status
Strong Privacy and Security Commitments
· No mining of customer data for advertising
· No voluntary disclosure to law enforcement agencies
Achieved
Contractual commitment to meet US and EU data residency requirements Achieved
ISO 27001 Achieved
ISO 27018 Achieved
EU Model Clauses (EUMC) Achieved
HIPAA Business Associate Agreement Achieved
PCI Started (in progress)
SOC 1 & SOC 2 Started (in progress)
FedRAMP, IRS 1075, UK Official (IL2) Started (in progress)
Health Information Trust Alliance (HITRUST) Planned

24. Recent Updates

25. DocumentDB Local Emulator
Free, downloadable, and high fidelity version of the cloud service for offline dev/test

26. Change Feed • Lambda pattern with significantly lower TCO
• Single scalable database solution for both ingestion and query

27. Q&A