Overview for The Budapest MUG

What’s New in MongoDB 3.2

MarcSchweringSr.Solu1onArchitect–EMEAe:marc@mongodb.comt:@m4rcsch

Storage Engines Broaden Use Cases

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

Man

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Sec

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In-memory (beta) Encrypted 3rd party

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

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

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

One Deployment Powering Multiple Apps

Built for Mission Critical Deployments

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

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

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

Tools for Users Across Your Organization

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

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

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

Conceptual Model of Aggregation 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

Conceptual Model of Aggregation 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

Improved In-Database Analytics & 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

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

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

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

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.

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

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

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

Thank you!

Marc Schwering

Sr. Solutions Architect – EMEA marc@mongodb.com

@m4rcsch