The key components of a distributed database system are on-demand capacity, high availability, and geographically distributed operations. In this session, learn how you can easily accomplish all three components when building out global databases using MongoDB Atlas (the official, fully managed MongoDB service) on AWS. If you’re looking to scale out your application to different parts of the world and/or have data sovereignty restrictions, this session can help you launch your next initiative. This presentation is brought to you by MongoDB, a member of the AWS Partner Network.

1. Building a Global Database with MongoDB Atlas
Eugene Kang, Sr. Solutions Architect, MongoDB
DEM16-S

2. 2
Key Components for a Distributed Database System
Geographically
Distributed
Operations
Distributed Database
High Availability On-Demand
Capacity

3. How can MongoDB help you build out
a globally distributed database?

4. Atlas
unlocks agility
and reduces
cost
Self-service and
elastic
Global and highly
available
Secure by default
Comprehensive
monitoring
Managed backup
Available in 60+
regions

5. High Availability

6. 6
High Availability
Requirements: ● Replication
● Multi-Region
● Automatic Failover

7. 7
Supports 2 to 50 copies
of data and is self-healing
Application
Driver
Primary
Secondary
Secondary
Replication
MongoDB Atlas makes it very simple
to deploy across regions!
High Availability

8. On-Demand Capacity

9. 9
Requirements: ● Vertical Scaling
● Horizontal Scaling
On-Demand Capacity

10. 10
On-Demand Capacity
Vertical Scaling:
Not just related to distributed
databases... More RAM, more
CPU, more disk, etc.

11. 11
On-Demand Capacity
Vertical Scaling
in MongoDB Atlas:
Pick your base hardware
configuration, e.g. RAM/CPU.
Fine-tune storage and IOPS
configurations.

12. 12
On-Demand Capacity
Horizontal Scaling:
Specific to distributed databases.
Cheaper hardware running in
parallel at web-scale.

13. 13
On-Demand Capacity
Horizontal Scaling
in MongoDB Atlas:
1) Extra secondary nodes for your
applications to read off of.

14. 14
On-Demand Capacity
Horizontal Scaling
in MongoDB Atlas:
2) Go a step further and create
hidden, non-electable, secondary
nodes for workload isolation and
extensive local reads.

15. 15
Co-locating operational and analytical workloads
Analytical
Primary Secondary Secondary Secondary
{use = analytics}
Transactional
BI & Reporting
Predictive Analytics
& Data Science
Aggregations
Secondary
{use = analytics}
Compass
BI Connector

16. Geographically Distributed
Operations

17. 17
Geographically Distributed Operations
Requirements: ● Write to many nodes
● Read from many nodes
○ Note: All nodes in any
MongoDB cluster are
readable. So we will focus
on writes.

18. 18
Global Writes in MongoDB Atlas:
1) Shard/partition your cluster, e.g. X number of replica sets.
Geographically Distributed Operations

19. 19
MongoDB Sharding Architecture
Application
Driver
Mongos
Primary
Secondary
Secondary
Shard 1
Primary
Secondary
Secondary
Shard 2
Primary
Secondary
Secondary
Shard N
Mongos ••••••
•••
High availability
- Replica sets
Horizontal scalability
- Sharding

20. 20
Global Writes in MongoDB Atlas:
2) Zone Sharding: logical zones that you define, e.g. country code, that contains
1 to many shards
Geographically Distributed Operations

21. Demo