What is new in MongoDB Version 3.2? A quick overview with high level topics and some details as dicussed at the MUG in Budapest.

1. Overview for
The Budapest MUG
What’s New in
MongoDB 3.2
Marc Schwering
Sr. Solu1on Architect – EMEA
e: marc@mongodb.com
t: @m4rcsch

2. Storage Engines Broaden Use Cases

3. Storage Engine Architecture in 3.2
Content
Repo
IoT Sensor
Backend
Ad Service
Customer
Analytics
Archive
MongoDB Query Language (MQL) + Native Drivers
MongoDB Document Data Model
WT MMAP
Supported in MongoDB 3.2
Management
Security
In-memory
(beta)
Encrypted 3rd party

4. WiredTiger is the New Default
WiredTiger – widely deployed with 3.0 – is
now the default storage engine for
MongoDB.
• Best general purpose storage engine
• 7-10x better write throughput
• Up to 80% compression

5. Encrypted Storage Engine
Encrypted storage engine for end-to-end
encryption of sensitive data in regulated
industries
• Reduces the management and performance
overhead of external encryption mechanisms
• AES-256 Encryption, FIPS 140-2 option available
• Key management: Local key management via
keyfile or integration with 3rd party key
management appliance via KMIP
• Offered as an option for WiredTiger storage engine

6. In-Memory Storage Engine (Beta)
Handle ultra-high throughput with low
latency and high availability
• Delivers the extreme throughput and predictable
latency required by the most demanding apps in
Adtech, finance, and more.
• Achieve data durability with replica set members
running disk-backed storage engine
• Available for beta testing and is expected for GA in
early 2016

7. One Deployment Powering MultipleApps

8. Built for Mission Critical Deployments

9. Data Governance with Document Validation
Implement data governance without
sacrificing agility that comes from dynamic
schema
• Enforce data quality across multiple teams and
applications
• Use familiar MongoDB expressions to control
document structure
• Validation is optional and can be as simple as a
single field, all the way to every field, including
existence, data types, and regular expressions

10. Document Validation Example
The example on the left adds a rule to the
contacts collection that validates:
• The year of birth is no later than 1994
• The document contains a phone number and / or
an email address
• When present, the phone number and email
addresses are strings

11. Enhancements for your mission-critical apps
More improvements in 3.2 that optimize the
database for your mission-critical
applications
• Meet stringent SLAs with fast-failover algorithm
– Under 2 seconds to detect and recover from
replica set primary failure
• Simplified management of sharded clusters
allow you to easily scale to many data centers
– Config servers are now deployed as replica
sets; up to 50 members

12. Tools for UsersAcross Your Organization

13. For Business Analysts & Data Scientists
MongoDB 3.2 allows business analysts and
data scientists to support the business with
new insights from untapped data sources
• MongoDB Connector for BI
• Dynamic Lookup
• New Aggregation Operators & Improved Text
Search

14. MongoDB Connector for BI
Visualize and explore multi-dimensional
documents using SQL-based BI tools. The
connector does the following:
• Provides the BI tool with the schema of the
MongoDB collection to be visualized
• Translates SQL statements issued by the BI tool
into equivalent MongoDB queries that are sent to
MongoDB for processing
• Converts the results into the tabular format
expected by the BI tool, which can then visualize
the data based on user requirements
⇒ h=ps://www.mongodb.com/download-center?jmp=hero#bi-connector

15. Dynamic Lookup
Combine data from multiple collections with
left outer joins for richer analytics & more
flexibility in data modeling
• Blend data from multiple sources for analysis
• Higher performance analytics with less application-
side code and less effort from your developers
• Executed via the new $lookup operator, a stage in
the MongoDB Aggregation Framework pipeline

16. Conceptual Model ofAggregation Framework
Start with the original collection; each record
(document) contains a number of shapes (keys),
each with a particular color (value)
• $match filters out documents that don’t contain a
red diamond
• $project adds a new “square” attribute with a
value computed from the value (color) of the
snowflake and triangle attributes

17. Conceptual Model ofAggregation Framework
• $lookup performs a left outer join with another
collection, with the star being the comparison key
• Finally, the $group stage groups the data by the
color of the square and produces statistics for
each group

18. Improved In-DatabaseAnalytics & Search
New Aggregation operators extend options for
performing analytics and ensure that answers
are delivered quickly and simply with lower
developer complexity
• Array operators: $slice, $arrayElemAt, $concatArrays,
$filter, $min, $max, $avg, $sum, and more
• New mathematical operators: $stdDevSamp,
$stdDevPop, $sqrt, $abs, $trunc, $ceil, $floor, $log,
$pow, $exp, and more
• Case sensitive text search and support for additional
languages such as Arabic, Farsi, Chinese, and more

19. For Database Administrators
MongoDB 3.2 helps users in your
organization understand the data in your
database
• MongoDB Compass
– For DBAs responsible for maintaining the
database in production
– No knowledge of the MongoDB query
language required

20. MongoDB Compass
For fast schema discovery and visual
construction of ad-hoc queries
• Visualize schema
– Frequency of fields
– Frequency of types
– Determine validator rules
• View Documents
• Graphically build queries
• Authenticated access
⇒ h=ps://www.mongodb.com/download-center?jmp=hero#compass

21. For Operations Teams
MongoDB 3.2 simplifies and enhances
MongoDB’s management platforms. Ops
teams can be 10-20x more productive using
Ops and Cloud Manager to run MongoDB.
• Start from a global view of infrastructure:
Integrations with Application Performance
Monitoring platforms
• Drill down: Visual query performance diagnostics,
index recommendations
• Then, deploy: Automated index builds
• Refine: Partial indexes improve resource
utilization

22. Integrations with APM Platforms
Easily incorporate MongoDB performance
metrics into your existing APM dashboards
for global oversight of your entire IT stack
• MongoDB drivers enhanced with new API that
exposed query performance metrics to APM tools
• In addition, Ops and Cloud Manager can
complement this functionality with rich database
monitoring.

23. Query Perf. Visualizations & Optimization
Fast and simple query optimization with the
new Visual Query Profiler
• Query and write latency are consolidated and
displayed visually; your ops teams can easily
identify slower queries and latency spikes
• Visual query profiler analyzes the data it displays
and provides recommendations for new indexes
that can be created to improve query performance
• Ops Manager and Cloud Manager can automate
the rollout of new indexes, reducing risk and your
team’s operational overhead

24. Refine with Partial Indexes
Balance delivering good query performance
while consuming fewer system resources
• Specify a filtering expression during index creation
to instruct MongoDB to only include documents
that meet your desired conditions
• The example to the left creates a compound index
that only indexes the documents with the rating
field greater than 5

25. Ops Manager Enhancements
3.2 includes Ops Manager enhancements to
improve the productivity of your ops teams and
further simplify installation and management
• MongoDB backup on standard network-mountable filesystems;
integrates with your existing storage infrastructure
• Automated database restores; Build clusters from backup in a
few clicks
• Faster time to first database snapshot
• Support for maintenance windows
• Centralized UI for installation and config of all application and
backup components

26. Thank you!
Marc Schwering
Sr. Solutions Architect – EMEA
marc@mongodb.com
@m4rcsch