The document discusses managing heterogeneous data stacks using Informatica and MongoDB Atlas, highlighting the challenges of data integration, the importance of cloud adoption, and the rise of machine learning in automating integration. It emphasizes the need for a unified metadata intelligence and offers solutions for operational data integration across hybrid and multi-cloud environments. The focus is on creating a complete and trusted view of customer data while addressing real-time and batch integration needs.

1. 1
Managing Heterogeneous Data Stacks With Informatica and
MongoDB Atlas
Seth Payne
Sr. Product Manager, MongoDB
Sumon Saha
Director of Product Management, Informatica
susaha@informatica.comseth.payne@mongodb.com

2. Best way to
work with data
Freedom to
run anywhere
Intelligently put data
where you need it
Intelligent Operational Data Platform

3. Data Source
Integration
Data
APIs
Data Loading
and
Streaming
Legacy
Systems
Offloading
Data
Analytics
Data
Governance

4. Massive volumes & large variety
Applications
Files
Images,
Audio & Video
Sensors
Tabular Databases
MongoDB &
Other Non Tabular
Data Warehouse &
Data Lake
Many structures and sources
Integration Challenges

5. Data Access
API
Change
Data
Capture
(CDC)
Extract
Transform
Load
(ETL)
MongoDB Cluster
Document Data Model
Distributed Systems
Architecture
Cloud | On-Premises
Operational Apps and
Systems of Record
Producers
Operational Data Layer
Consumers
Mainframe Systems
CRM
ERP
Order Management
Supply Chain Mgmt
Data Lake
Marketing Automation
Website
Social Media
Reference Data
Third-Party APIs
Etc.
Batch Load
API CallsBatch File
Exports
Real-Time
Data Changes
Delta Load
MongoDB Change Streams
Write Back to Producer Systems (Optional)
MongoDB
Native Drivers
Consuming Operational
Apps and Services
Internal apps, customer-facing
services, and APIs for
third-party consumption – across
any channel
Business Intelligence (BI)
and Advanced Analytics
Visualization and reporting,
data analysis, artificial
intelligence, machine learning
and more
Human Capital Mgmt
MongoDB Connectors

6. MongoDB Connectors

8. of enterprise workloads
will be in the cloud by
2020
83%
Cloud is the Key Enabler of the New Digital Era
Source: Forbes, Logic Monitor Cloud Adoption

9. of large organizations
will enable their non-IT
personnel to perform
integration tasks by 2023*
65%
Democratization Empowers New Integration Personas
*Gartner, Predicts 2019: Democratization of IT Requires Different Strategies for Integration, Keith Guttridge, et al, 21 January 2019

10. of integration platforms will
leverage machine learning to
automate integration between
application APIs by 2020, thus
reducing the need for skilled
integration specialists*
75%
AI/ML Automates Integration
*Gartner, Predicts 2019: Democratization of IT Requires Different Strategies for Integration, Keith Guttridge, et al, 21 January 2019

11. SaaS, IaaS and PaaS Adoption Accelerating Rapidly
*CAGR 2017-2022 (%)
*Source: Gartner, Forecast Analysis: Public Cloud Services, Worldwide, 4Q18 Update, Colleen Graham, et al 8 Feb 2019
17%
Replace
Software as a Service
SaaS
Re-host
Infrastructure as a Service
IaaS
26.4% 20.2%
Re-platform
Platform as a Service
PaaS
Gartner estimates the following growth

12. of enterprises are looking
at a multi-cloud strategy;
with an average of 5
clouds
81%
Multi-Cloud and Hybrid is the Current Reality
Source: Rightscale 2018 state of Cloud Report

13. ML based
Integration
Re-platform
Replace
Rehost
New Data
New
Users
Hybrid
More
Workloads

14. Data Challenges Rise in a Multi-Cloud Hybrid World
Integrating business
processes that
span clouds
Data management
challenges amplify
with multiple clouds
Locked in by a
single best-of-breed
cloud provider
Challenges
Cloud
DW
Cloud
Application
Integration
Cloud B2B
Integration
Cloud
Data Lake
Cloud API
Mgmt.
Cloud
Migration
AWS RedshiftAmazon Aurora

15. Our Vision
ANY Integration Pattern ANY User ANY Data
Enterprise Unified Metadata Intelligence
Unified Modular Hybrid Secure Trusted iPaaS

16. Supporting Any Integration and Any Data
Management Pattern
Log data
Machine
& IOT
EDI order
requests
Website & Mobile
Edge Data
Streaming
Edge Data
Streaming
Big Data
Streaming
Queue
B2B
API order
requests
Place
an Order
API Gateway
Providers
On-Prem
ERP System
Data
Warehouses
Integration
Hub
Databases
Data
Integration
Data & Application
Integration
Application
Integration
API
API
API
API

17. Supporting Any Integration and Any Data
Management Pattern
Log data
Log data
EDI order
requests
Website
Edge Data
Streaming
Edge Data
Streaming
Big Data
Streaming
Queue
B2B
API order
requests
Place
an Order
API Gateway
Providers
On-Prem
ERP System
Data
Warehouses
Integration
Hub
Databases
Data
Integration
Data & Application
Integration
Application
Integration
API
API
API
API
Table stakes
Cloud Data
Integration
Cloud Application
Integration
Cloud API
Management
Connectivity
+
New and unique patterns
Cloud
B2B
Cloud
Integration Hub
Cloud
MDM
Cloud
Data Security
Cloud Data
Quality
Cloud Data
Preparation
Data Ingestion/
Data Lakes
Cloud
Streaming/IoT
Cloud Data
Catalog
Cloud Data
Governance

18. Connect Your Enterprise to Everything
Connecting 100,000 applications, databases, and other endpoints

19. Informatica MDM Services and
MongoDB Atlas

20. IICS MDM Services
Deliver a complete and trusted view of all enterprise customer data
Remove duplicate, inaccurate,
incomplete customer data
Customer data integration for a
complete view of across all data
sources and apps
Link trusted customer profiles
and explore relationships
Customer
360

21. IICS MDM - Architecture

22. Data Integration Modernization

23. Cloud Data Integration Modernization Blueprint
Supporting Any Modern Analytics
ENTERPRISE DATA CATALOG
DATA QUALITY & GOVERNANCE
DATA PROTECTION
Elastic Compute
API & Application Integration
Cloud Data Integration
Replication & Mass Ingestion
File & Streaming Ingestion Cloud Data Integration
Cloud
SaaS
LogsMachine
Data
Connected
Devices
Edge
DatabasesApplication
Servers
Mainframe
On-Premises
Cloud
Object Store
Cloud Data
Lake
Cloud Data
Warehouses
Machine
Learning
Visualization
Business
Intelligence

24. Data Integration Services
Use Cases: Data ingestion, migration, synchronization, replication
Synchronize SaaS and
On-premises Data
• Periodically sync SaaS and
on-premises applications to
Cloud DB/DW
• Cloud Data stores are used
for operational and analytic
purposes.
• Sync needs are both real
time as well as batch
Replicate Bulk Data to
Cloud
• Replicate on-premises data
to DB/DW on Cloud
• Cost savings and High
Availability
• Build using easy-to-use
wizards
Data Ingestion to
Databases and
Applications
• Bulk ingestion of data
sources
• Involves reuse of common
integration patterns like
Slowly Changing Dimensions,
error handling, etc.
• Migrate existing on-premises
DB/DW to cloud DB/DW

25. Application Integration and API Management Services
Use Cases: Real-time, API, and process integration needs
• Integrate API-based
applications in real time via
APIs and messaging
• Supplement bulk data
integration of data sets with
real-time data processing
• Integrate with MOM brokers
and ESB
Real-time Data Integration
• Create composite service and
data APIs exposed as REST,
SOAP, or OData services
• Expose managed APIs to
partners, customers, and
internal consumers
• Obtain visibility and control of
the use of APIs
API Creation and
Management
• Automate application and
business processes
• Provide interactive access to
data to users and applications
via API-enabled services and
data sources
• Provide users with automated
and guided workflows
Process Automation

26. Demonstration of
IICS Data Catalog & Data
Integration Services
w/ MongoDB integration

27. These graphics were published by Gartner, Inc. as part of larger research documents and should be evaluated in the context of the entire document. The Gartner
documents are available upon request from Informatica. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not
advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner's
research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including
any warranties of merchantability or fitness for a particular purpose.
A Leader in Five Gartner Magic Quadrants
Magic Quadrant
for Master Data
Management
Solutions
Michael Moran, et al.,
12 December 2018
Magic Quadrant
for Data
Integration Tools
Mark A. Beyer , et al.,
19 July 2018
Magic Quadrant
for Metadata
Management
Solutions
Guido De Simoni, et al.,
09 August 2018
Magic Quadrant
for Data Quality
Tools
Melody Chien, et al.,
27 March 2019
Magic Quadrant
for Enterprise
Integration Platform
as a Service
Eric Thoo, et al.,
23 April 2019
July 2018Aug 2018
March 2019 Dec 2018Apr 2019

28. 8T+
Transactions
per month
>300%
Growth of
API volume
7M+
Integrations/day
200%+ growth YoY
110+
OEMs
220+
Native Connectors
>50%
Annual revenue
growth
Volumes of data
2x
Every 6 months
Informatica Intelligent Cloud Services
• Connecting 100,000 applications, databases, and other endpoints

29. Informatica and MongoDB —
Better Together
• Complete—End to End Solution
Enterprise Cloud Data Management including
Data Integration, Quality, Governance and Master
Data Management
Streaming
Application Integration and API Management Solution
Support across hybrid and multi-cloud
• Speed—Time to Insights/Productivity
Automation and self-service
200+ codeless connectors
Metadata-driven development
• Fast—High Performance
Optimized, scalable, native integration

30. Questions?
Please visit us at the Drivers and Connectors Booth!