MongoDB 3.2 Preview

MongoDB 3.2 – a BIG Release

Hash-Based Sharding Roles Kerberos On-Prem Monitoring

2.2 2.4 2.6 3.0 3.2

Agg. Framework Location-Aware Sharding

$out Index Intersection Text Search Field-Level Redaction LDAP & x509 Auditing

Document Validation Fast Failover Simpler Scalability Aggregation ++ Encryption At Rest In-Memory Storage Engine BI Connector $lookup MongoDB Compass APM Integration Profiler Visualization Auto Index Builds Backups to File System

Doc-Level Concurrency Compression Storage Engine API ≤50 replicas Auditing ++ Ops Manager

Themes

Themes Broader use case portfolio. Pluggable storage engine strategy enables us to rapidly cover more use cases with a single database.

Mission-critical apps. MongoDB delivers major advances in the critical areas of

governance, high availability, and disaster recovery. New tools for new users. Now MongoDB is an integral part of the tooling and

workflows of Data Analysts, DBAs, and Operations teams.

Storage Engines

6

Varying Access & Storage Requirements

Modern apps

Sensitive data

Cost effective storage

High concurrency

High throughput

Low latency

Real-time analytics

7

Flexible Storage Architecture in 3.2

8

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

9

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

•  Based on WiredTiger storage engine

•  Requires MongoDB Enterprise Advanced

10

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

Document Validation

12

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

13

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

14

Document Validation

What you get •  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. More power to the DBAs •  The DBA can specify which documents in a collection should be validated •  Failed validations can be configured

–  Hard error –  Just a warning

Shard Cluster Improvements

16

Simplified Sharded Cluster Management

What you get •  Simplified sharded deployments

–  Config servers are deployed as replica sets •  Improved metadata consistency •  Easily scale to many data centers

Config server replica sets can span more than 3 data centers with up to 50 replica set members supported

Enhancements for your mission-critical apps More improvements in 3.2 that optimize the database for your mission-critical applications

•  Meet stringent SLAs with Raft-base fast-failover

algorithm

–  Under 2 seconds to detect and recover from

replica set primary failure

–  Enhanced durability through write conerns

•  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/locations

19

Fast Failover

The Improvements •  Enhanced algorithm detects failure and isolation of primary in replica set

–  Reduces interval between primary failure and the replacement –  Resolves false-positives caused by network glitches –  Allows efficient intra-cluster communications, even as the replica set grows

What you get •  No more than 2 seconds to detect and recover replica set primary failure

–  Exact time is dependent on system configuration –  Tune the timing with the electionTimeoutMillis parameter

•  Clusters more resilient to overloaded or unreliable networks

New Tools for New Users

DBAs 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

Operations

Integration with standard operational workflow reduces overhead •  Start from global view of infrastructure: APM tools

integration, e.g. New Relic, AppDynamics. •  Then, drill down: Profiler visualization in Ops Manager •  Then, deploy: Automated index builds •  Next, refine: Partial Indexes improve resource utilization

23

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

24

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

25

Dynamic Lookup

Combine data from multiple collections

with left outer joins for richer analytics &

more flexibility in data modeling

•  Blend data from multiple collections 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

26

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

•  Random sample of documents: $sample

•  Case sensitive text search and support for additional

languages such as Arabic, Farsi, Chinese, and more

27

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

28

Next Steps

•  Download the Whitepaper –  https://www.mongodb.com/collateral/mongodb-3-2-whats-new

•  Read the Release Notes –  https://docs.mongodb.org/manual/release-notes/3.2/

•  Not yet ready for production but download and try! –  https://www.mongodb.org/downloads#development

•  Detailed blogs –  https://www.mongodb.com/blog/

•  Feedback –  MongoDB 3.2 Bug Hunt

•  https://www.mongodb.com/blog/post/announcing-the-mongodb-3-2-bug-hunt –  https://jira.mongodb.org/

DISCLAIMER: MongoDB's product plans are for informational purposes only. MongoDB's plans may change and you should not rely on them for delivery of a specific feature at a specific time.

http://cl.jroo.me/z3/v/D/C/e/a.baa-Too-many-bicycles-on-the-van.jpg

Norberto Leite Technical Evangelist norberto@mongodb.com @nleite

Obrigado!