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Data Streaming with Apache Kafka & MongoDB Andrew Morgan – MongoDB Product Marketing David Tucker – Director, Partner Engineering and Alliances at Confluent 8 th November 2016
Transcript

Data Streaming with Apache Kafka &

MongoDB

Andrew Morgan – MongoDB Product MarketingDavid Tucker – Director, Partner Engineering

and Alliances at Confluent

8th November 2016

Agenda

Target Audience

Apache Kafka

MongoDB

Integrating MongoDB and Kafka

Kafka – What’s Next

Next Steps

Target Audience

Target Audience

Target Audience

Target Audience

Target Audience

Target Audience

Apache Kafka / Confluent Platform

What does Kafka do?

Producers

Consumers

Kafka Connect

Kafka Connect

Topic

Your interfaces to the world

Connected to your systems in real time

What is Streaming Data

Synchronous Req/Response0 – 100s ms

Near Real Time> 100s ms

Offline Batch> 1 hour

KAFKAStream Data Platform

Search

RDBMS

Apps Monitoring

Real-time AnalyticsNoSQL Stream Processing

HADOOPData Lake

Impala

DWH

Hive

Spark Map-Reduce

Confluent’s OfferingsCore

Connect

Streams

Java Client

Kafka

Confluent Platform EnterpriseConfluent Platform

Multi-data-center ReplicationMore Clients

Advanced Data BalancingREST Proxy

Stream MonitoringSchema Registry

Connector ManagementPre-Built Connectors

Confluent Platform: It’s Kafka ++Feature Benefit Apache Kafka Confluent Open

Source Confluent Enterprise

Apache Kafka High throughput, low latency, high availability, secure distributed message system

Kafka Connect Advanced framework for connecting external sources/destinations into Kafka

Kafka Streams Simple library that enables streaming application development within the Kafka framework

Additional Clients Supports non-Java clients; C, C++, Python, etc.

REST Proxy Provides universal access to Kafka from any network connected device via HTTP

Schema Registry Central registry for the format of Kafka data – guarantees all data is always consumable

Pre-Built Connectors HDFS, JDBC, elasticsearch and other connectors fully certified and fully supported by Confluent

Confluent Control Center Enables easy connector management and stream monitoring

Data Center & Cloud MDC Replication, auto-data balancing

Support Enterprise class support to keep your Kafka environment running at top performance Community Community 24x7x365

Free Free Subscription

Common Kafka Use Cases

Data transport and integration• Log data• Database changes• Sensors and device data• Monitoring streams• Call data records• Stock ticker data

Real-time stream processing• Monitoring• Asynchronous applications• Fraud and security

Kafka Adoption in Large Enterprises

6 of the top 10 travel companies

8 of the top 10 insurance companies

7 of the top 10 global banks

9 of the top 10telecom companies

People Using Kafka TodayFinancial Services

Entertainment & Media

Consumer Tech

Travel & Leisure

Enterprise Tech

Telecom Retail

MongoDB

Relational

Expressive Query Language& Secondary Indexes

Strong Consistency

Enterprise Management& Integrations

The World Has ChangedData Risk

Time Cost

NoSQL

Scalability& Performance

Always On,Global Deployments

FlexibilityExpressive Query Language& Secondary Indexes

Strong Consistency

Enterprise Management& Integrations

Nexus Architecture

Scalability& Performance

Always On,Global Deployments

FlexibilityExpressive Query Language& Secondary Indexes

Strong Consistency

Enterprise Management& Integrations

Integrating MongoDB and Kafka

Where MongoDB Fits

Prod324

123...

Topic A

Prod967

123...

Topic B

Filter

Filter

Merge534

123...

Topic C

Analyze496

123...

Topic D

TakeAction

Take Action

Where MongoDB Fits

Prod324

123...

Topic A

Prod967

123...

Topic B

Filter

Filter

Merge534

123...

Topic C

Analyze496

123...

Topic D

TakeAction

StoreResults

Operational Database

Where MongoDB Fits

Prod324

123...

Topic A

Prod967

123...

Topic B

Filter

Filter

Merge534

123...

Topic C

Analyze496

123...

Topic D

TakeAction

StoreResults

KeyEvents

Operational Database

Where MongoDB Fits

Prod324

123...

Topic A

Prod967

123...

Topic B

Filter

Filter

Merge534

123...

Topic C

Analyze496

123...

Topic D

TakeAction

StoreResults

KeyEvents

Operational Database

Where MongoDB Fits

Prod324

123...

Topic A

Prod967

123...

Topic B

Filter

Filter

Merge534

123...

Topic C

Analyze496

123...

Topic D

TakeAction

StoreResults

KeyEvents

Operational Database

Reference Data

Where K-Streams Fits

Prod324

123...

Topic A

Prod967

123...

Topic B

534

123...

Topic C

Analyze496

123...

Topic D

TakeAction

StoreResults

KeyEvents

Operational Database

Reference Data

Kafka Streams

MongoDB As a Kafka Producer

Mes

sage

Que

ue

Customer Data Mgmt Mobile App IoT App Live Dashboards

Raw Data

Processed Events

Distributed Processing Frameworks

Millisecond latency. Expressive querying & flexible indexing against subsets of data. Updates-in place. In-database aggregations & transformations

Multi-minute latency with scans across TB/PB of data. No indexes. Data stored in 128MB blocks. Write-once-read-many & append-only storage model

Sensors

User Data

Clickstreams

Logs

Churn Analysis

Enriched Customer Profiles

Risk Modeling

Predictive Analytics

Real-Time Access

Batch Processing, Batch Views

Design Pattern: Operationalized Data Lake

Kafka Streams

Mes

sage

Que

ue

Customer Data Mgmt Mobile App IoT App Live Dashboards

Raw Data

Processed Events

Millisecond latency. Expressive querying & flexible indexing against subsets of data. Updates-in place. In-database aggregations & transformations

Multi-minute latency with scans across TB/PB of data. No indexes. Data stored in 128MB blocks. Write-once-read-many & append-only storage model

Sensors

User Data

Clickstreams

Logs

Churn Analysis

Enriched Customer Profiles

Risk Modeling

Predictive Analytics

Real-Time Access

Batch Processing, Batch Views

Design Pattern: Operationalized Data LakeConfigure where to land incoming data

Distributed Processing Frameworks

Kafka Streams

Mes

sage

Que

ue

Customer Data Mgmt Mobile App IoT App Live Dashboards

Raw Data

Processed Events

Millisecond latency. Expressive querying & flexible indexing against subsets of data. Updates-in place. In-database aggregations & transformations

Multi-minute latency with scans across TB/PB of data. No indexes. Data stored in 128MB blocks. Write-once-read-many & append-only storage model

Sensors

User Data

Clickstreams

Logs

Churn Analysis

Enriched Customer Profiles

Risk Modeling

Predictive Analytics

Real-Time Access

Batch Processing, Batch Views

Design Pattern: Operationalized Data Lake

Raw data processed to generate analytics models

Distributed Processing Frameworks

Kafka Streams

Mes

sage

Que

ue

Customer Data Mgmt Mobile App IoT App Live Dashboards

Raw Data

Processed Events

Millisecond latency. Expressive querying & flexible indexing against subsets of data. Updates-in place. In-database aggregations & transformations

Multi-minute latency with scans across TB/PB of data. No indexes. Data stored in 128MB blocks. Write-once-read-many & append-only storage model

Sensors

User Data

Clickstreams

Logs

Churn Analysis

Enriched Customer Profiles

Risk Modeling

Predictive Analytics

Real-Time Access

Batch Processing, Batch Views

Design Pattern: Operationalized Data LakeMongoDB exposes analytics models to operational apps. Handles real time

updates

Distributed Processing Frameworks

Kafka Streams

Mes

sage

Que

ue

Customer Data Mgmt Mobile App IoT App Live Dashboards

Raw Data

Processed Events

Millisecond latency. Expressive querying & flexible indexing against subsets of data. Updates-in place. In-database aggregations & transformations

Multi-minute latency with scans across TB/PB of data. No indexes. Data stored in 128MB blocks. Write-once-read-many & append-only storage model

Sensors

User Data

Clickstreams

Logs

Churn Analysis

Enriched Customer Profiles

Risk Modeling

Predictive Analytics

Real-Time Access

Batch Processing, Batch Views

Design Pattern: Operationalized Data LakeCompute new

models against MongoDB &

HDFS

Distributed Processing Frameworks

Kafka Streams

Kafka – What’s Next

Kafka Connectors• Confluent-supported connectors (included in CP)

• Community-written connectors (just a sampling)

JDBC

Kafka Futures• Apache Core

• Admin API (KIP-4)• Exactly-once delivery semantics• Time-based topic indexing

• Kafka Streams• Exactly-once processing semantics• Interactive Queries: enable real-time sharing of application state with

other applications• Confluent Platform Enterprise

• Multi-cluster views and expanded alerting added to Control Center

Next Steps

MongoDB AtlasDatabase as a service for MongoDB

MongoDB Atlas is…

• Automated: The easiest way to build, launch, and scale apps on MongoDB

• Flexible: The only database as a service with all you need for modern applications

• Secured: Multiple levels of security available to give you peace of mind

• Scalable: Deliver massive scalability with zero downtime as you grow

• Highly available: Your deployments are fault-tolerant and self-healing by default

• High performance: The performance you need for your most demanding workloads

MongoDB Atlas Features

• Spin up a cluster in minutes

• Replicated & always-on deployments

• Fully elastic: scale out or up in a few clicks with zero downtime

• Automatic patches & simplified upgrades for the newest MongoDB features

• Authenticated & encrypted

• Continuous backup with point-in-time recovery

• Fine-grained monitoring & custom alerts

Safe & SecureRun for You

• On-demand pricing model; billed by the hour

• Multi-cloud support (AWS available with others coming soon)

• Part of a suite of products & services designed for all phases of your app; migrate easily to different environments (private cloud, on-prem, etc) when needed

No Lock-In

Database as a service for MongoDB

MongoDB Enterprise Advanced

• MongoDB Ops Manager or MongoDB Cloud Manager Premium

• MongoDB Compass

• MongoDB Connector for BI

• Cloud Foundry Integration

• Encrypted Storage Engine

• LDAP / Kerberos Integration

• DDL & DML Auditing

• FIPS 140-2 Support

SecurityTooling

• 24 x 7 Support

• 1 hr SLA

• Emergency Patches

• Customer Success Program

• On-Demand Training

Support License

• Commercial License

Old Billingsgate, London15th November

mongodb.com/europe

Use my discount code for 20% off: andrewmorgan20


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