SlideShare una empresa de Scribd logo
1 de 22
Descargar para leer sin conexión
Confidential and Proprietary. Do not distribute without Couchbase consent. © Couchbase 2017. All rights reserved.
Milliarden von Messages in
Echtzeit: Warum Paypal &
LinkedIn auf eine
Engagement-Datenbank
vertrauen
09.10.2018
Bruno Šimić – Solutions Engineer
ATTRIBUTES OF AN
ENGAGEMENT DATABASE
Always on,
always fast
Secure, secure,
secure
Built-in
smarts
Seamlessly
mobile
Hello cloud,
hello world
Built for change
- at scale
Why
Customers
Choose
Couchbase?
Memory-first
Architecture
Full SQL Query
Language
Active-Active
Global Data
Replication
Multi-dimensional
scaling
Mobile
Confidential and Proprietary. Do not distribute without Couchbase consent. © Couchbase 2018. All rights reserved.
Core Principles of Couchbase
Platform Evolution
Started with Core Principles
– True auto sharding
– JSON-based flexible data model
– Memory-first Architecture
– Asynchronous approach to everything
– Scale workloads independently
Managed
Cache
Key-Value
Store
Document
Database Mobile
N1QL
Query
Full Text
Search Analytics
Confidential and Proprietary. Do not distribute without Couchbase consent. © Couchbase 2017. All rights reserved.
Confidential and Proprietary. Do not distribute without Couchbase consent. © Couchbase 2018. All rights reserved. 6Confidential and Proprietary. Do not distribute without Couchbase consent. © Couchbase 2018. All rights reserved.
Couchbase
Hybrid / Multi-Cloud Data
Platform
• Service-Centric Clustered Data System
- Multi-process Architecture
- Dynamic Distribution of Facilities
- Cluster Map Distribution
- Automatic Failover
• Offline Mobile Data Integration
• N1QL - SQL-like Query Engine for JSON
• Global Secondary Indexes
• Lowest Latency Key-Value API
• Active-Active Inter-DC Replication
• Full-Text Search
• Eventing
• Operational Analytics
On-premPrivate Cloud
AWSAzure
GCP
Eventing
Mobile Query
Key
Value
Analytics
Indexing
Full Text
Search
Couchbase designed for containerized applications
Introducing Couchbase Autonomous Operator
Couchbase Autonomous Operator is an application-specific controller that extends the
Kubernetes API to create, configure and manage instances of complex stateful applications
on behalf of a Kubernetes user.
It builds upon the basic Kubernetes resource and controller concepts, but also includes
domain or application-specific knowledge to automate common tasks better managed by
computers.
Couchbase K8 operator Architecture
Next Generation Data Management Architecture
Data
Sources
Enterprise
Applications
Social Media
Web &
Ecommerce
Mobile AppsSensor Data MainframeExternal DataSystem Logs
Data
Integration
Speed Layer Batch Layer
Data
Management
Data Lake Data Warehouse
Business Intelligence Dashboards Query ToolsData
Access
In Memory Cache
Data Serving Layer
Next Generation Data Management Architecture
Enterprise
Applications
Social Media
Web &
Ecommerce
Mobile AppsSensor Data MainframeExternal DataSystem Logs
Speed Layer Batch Layer
Data Lake
Business Intelligence Dashboards Query Tools
In Memory Cache
Data Warehouse
N1QL Query Workbench
Data
Sources
Data
Integration
Data
Management
Data
Access
Data Serving Layer
Real Time
Data Ingestion
Ingest, Process, Load and Serve Data at global scale
Confidential and Proprietary. Do not distribute without Couchbase consent. © Couchbase 2018. All rights reserved.
Kafka Connect Couchbase
Connector 3.4
Confidential and Proprietary. Do not distribute without Couchbase consent. © Couchbase 2018. All rights reserved.
• Use Couchbase as either a consumer or producer with Kafka
message queues
• Continuous streaming, filter, and transformation of events to and
from Couchbase with Source and Sink connectors.
• Fast, reliable and fault tolerant: Based on DCP (Couchbase
replication protocol).
• Efficient: Only load new or modified documents.
• Real-time: Every mutation to Couchbase generates an event
which is published to a Kafka topic.
• Compression and IPv6 support
• Support for rollback mitigation
Couchbase cluster
…
Kafka cluster
Kafka Connect
(Connectors to Extract and Load data)
Confluent and Couchbase - Synergies
Confidential and Proprietary. Do not distribute without Couchbase consent. © Couchbase 2018. All rights reserved.
• Distributed and fault tolerant
• Horizontally scalable
• Geographically replicated
• Low latency
• Open source
Customer Spotlight
1.1 trillion hits a day
75% of flight bookings
worldwide are made
through Amadeus
50M Unique
monthly visitors
2.5B monthly page views
Replaced MongoDB
2821 nodes, 100+ clusters
16M entries every 5 min
2.5 millon ops/sec. on a
single cluster
1 billion+ documents
10TB+ data
Sub-2oo ms
response time
E-Commerce Travel CommunicationsGaming
Financial Services Health Industrial IoTDigital Media
17
Objectives & Challenges
Provide business users with real
time reports and visualizations of
user interaction data
• Collect web and mobile clickstream in
real time
• Integrate with other big data
technologies (Hadoop and Storm)
• Provide views of data across
multiple dimensions (e.g., time,
location, browser and device types)
Solution
Deploy Couchbase Server to capture,
store, and process real time web data
• Ingests data (via Storm) from
multiple inputs, including mobile,
web, and other services, storing
data as JSON documents
• Integrates with Hadoop to pass data
for additional offline analytics
• 130m+ active
accounts, in 190+
countries, 25
currencies
• 10TB data
• 1B documents
The Couchbase
Advantage
Real time performance,
easy integration with Kafka, Storm
and Hadoop
Confidential and Proprietary. Do not distribute without
Couchbase consent. © Couchbase 2018. All rights reserved.
User Activity Tracking
and real-time analytics
@ Paypal
Results
• Consistent low latency
(sub 10-msec response)
• High availability enabled by
distributed caching and XDCR
• Views for business users are
generated in under 1 minute,
based on 10-minute data
collection intervals
17
Objectives & Challenges
Read scaling and TCO becomes
important
• Constant growth of user profiles,
groups, jobs and publications
• Difficult to move data across data
centers
• Very complex administration of the
system
• Risk of security breach by using
many different components
Solution
Deploy Couchbase Server to cache,
store and replicate data in real time
with low latency
• One singe solution for in memory
caching, ephemeral counter store,
temporary de-duping store and SoT
for internal tooling
• Center of excellence for
Couchbase within Linkedin created
• LinkedIn build ist own NoSQL
databas (Voldemort), Couchbase is
still used as the main database for
this use cases
• 560M users, 26M
companies, 15M
active jobs listings
• 1.5B documents in
cluster
• 10M queries/sec
• 30 Offices in 24
countries
• 24 languages
Confidential and Proprietary. Do not distribute without
Couchbase consent. © Couchbase 2018. All rights reserved.
Read scaling & data
replication across DCs
worldwide
Results
• Consistent low latency
• High availability enabled by
distributed caching and
XDCR
• Higher acceptance at users
• Scalable and performant
system with zero downtime
• Lower TCO
Additional information
Confidential and Proprietary. Do not distribute without Couchbase consent. © Couchbase 2018. All rights reserved.
Couchbase Mobile: The Full-Stack
Mobile Data Platform
Confidential and Proprietary. Do not distribute without Couchbase consent. © Couchbase 2018. All rights reserved.
Lightweight embedded NoSQL database
with full CRUD and query functionality.
Secure web gateway with synchronization, data access,
and data integration APIs for accessing, integrating, and
synchronizing data over the web.
Highly scalable, highly available, high
performance NoSQL database server.
Built-in enterprise level security throughout the entire stack includes user authentication, user and role based
data access control (RBAC), secure transport (TLS), and 256-bit AES full database encryption.
Couchbase Lite Sync Gateway Couchbase Cluster
SECURITY
EMBEDDED DATABASE SYNCHRONIZATION DATABASE SERVERCLIENT WEB TIER DATABASEinternet intranet
Developing
with
Couchbase
Confidential and Proprietary. Do not distribute without Couchbase consent. © Couchbase 2018. All rights reserved.
Couchbase supports a wide
range of frameworks,
languages, platforms and
infrastructure choices.
FRAMEWORKS LANGUAGES PLATFORMS INFRASTRUCTURE
MOBILEMOBILE
Services & Training geared to customer
success
2
3
Professional Services
• Center of Excellence with product experts
• Packaged Services
• Workshops
• Custom Consulting
• Comprehensive NoSQL & Couchbase training
• Hands-on, intensive labs
• Best practices based on 100s of real use cases
• Developer and Admin courses
• Global Couchbase facilities, or at customer site
Learning Services
Email inquiries: Services@couchbase.com
Visit us: http://www.couchbase.com/couchbase-services
Email inquiries: Training@couchbase.com
Visit us: http://training.couchbase.com
Additional Resources
• Kafka connector:
https://docs.couchbase.com/kafka-
connector/3.4/index.html
• Blog:
http://blog.couchbase.com
• Forum:
http://forums.couchbase.com
• General Docs:
http://docs.couchbase.com
• Developer Portal:
http://developer.couchbase.com
• Couchbase Labs:
https://github.com/couchbaselabs
• Query Portal:
http://query.couchbase.com
Confidential and Proprietary. Do not distribute without Couchbase consent. © Couchbase 2018. All rights reserved.
Thank you
22

Más contenido relacionado

La actualidad más candente

Going from three nines to four nines using Kafka | Tejas Chopra, Netflix
Going from three nines to four nines using Kafka | Tejas Chopra, NetflixGoing from three nines to four nines using Kafka | Tejas Chopra, Netflix
Going from three nines to four nines using Kafka | Tejas Chopra, Netflix
HostedbyConfluent
 
Moving 150 TB of data resiliently on Kafka With Quorum Controller on Kubernet...
Moving 150 TB of data resiliently on Kafka With Quorum Controller on Kubernet...Moving 150 TB of data resiliently on Kafka With Quorum Controller on Kubernet...
Moving 150 TB of data resiliently on Kafka With Quorum Controller on Kubernet...
HostedbyConfluent
 
Bringing Streaming Data To The Masses: Lowering The “Cost Of Admission” For Y...
Bringing Streaming Data To The Masses: Lowering The “Cost Of Admission” For Y...Bringing Streaming Data To The Masses: Lowering The “Cost Of Admission” For Y...
Bringing Streaming Data To The Masses: Lowering The “Cost Of Admission” For Y...
confluent
 
MongoDB Breakfast Milan - Mainframe Offloading Strategies
MongoDB Breakfast Milan -  Mainframe Offloading StrategiesMongoDB Breakfast Milan -  Mainframe Offloading Strategies
MongoDB Breakfast Milan - Mainframe Offloading Strategies
MongoDB
 

La actualidad más candente (20)

Going from three nines to four nines using Kafka | Tejas Chopra, Netflix
Going from three nines to four nines using Kafka | Tejas Chopra, NetflixGoing from three nines to four nines using Kafka | Tejas Chopra, Netflix
Going from three nines to four nines using Kafka | Tejas Chopra, Netflix
 
Kafka and Kafka Streams in the Global Schibsted Data Platform
Kafka and Kafka Streams in the Global Schibsted Data PlatformKafka and Kafka Streams in the Global Schibsted Data Platform
Kafka and Kafka Streams in the Global Schibsted Data Platform
 
Moving 150 TB of data resiliently on Kafka With Quorum Controller on Kubernet...
Moving 150 TB of data resiliently on Kafka With Quorum Controller on Kubernet...Moving 150 TB of data resiliently on Kafka With Quorum Controller on Kubernet...
Moving 150 TB of data resiliently on Kafka With Quorum Controller on Kubernet...
 
Data in Motion: Building Stream-Based Architectures with Qlik Replicate & Kaf...
Data in Motion: Building Stream-Based Architectures with Qlik Replicate & Kaf...Data in Motion: Building Stream-Based Architectures with Qlik Replicate & Kaf...
Data in Motion: Building Stream-Based Architectures with Qlik Replicate & Kaf...
 
First Steps with Apache Kafka on Google Cloud Platform
First Steps with Apache Kafka on Google Cloud PlatformFirst Steps with Apache Kafka on Google Cloud Platform
First Steps with Apache Kafka on Google Cloud Platform
 
Building Microservices with Apache Kafka by Colin McCabe
Building Microservices with Apache Kafka by Colin McCabeBuilding Microservices with Apache Kafka by Colin McCabe
Building Microservices with Apache Kafka by Colin McCabe
 
Kafka Summit SF 2017 - Fast Data in Supply Chain Planning
Kafka Summit SF 2017 - Fast Data in Supply Chain PlanningKafka Summit SF 2017 - Fast Data in Supply Chain Planning
Kafka Summit SF 2017 - Fast Data in Supply Chain Planning
 
Kafka Summit SF 2017 - Riot's Journey to Global Kafka Aggregation
Kafka Summit SF 2017 - Riot's Journey to Global Kafka AggregationKafka Summit SF 2017 - Riot's Journey to Global Kafka Aggregation
Kafka Summit SF 2017 - Riot's Journey to Global Kafka Aggregation
 
Creating a Kafka Topic. Super easy? | Andrew Stevenson and Marios Andreopoulo...
Creating a Kafka Topic. Super easy? | Andrew Stevenson and Marios Andreopoulo...Creating a Kafka Topic. Super easy? | Andrew Stevenson and Marios Andreopoulo...
Creating a Kafka Topic. Super easy? | Andrew Stevenson and Marios Andreopoulo...
 
It's Time To Stop Using Lambda Architecture | Yaroslav Tkachenko, Shopify
It's Time To Stop Using Lambda Architecture | Yaroslav Tkachenko, ShopifyIt's Time To Stop Using Lambda Architecture | Yaroslav Tkachenko, Shopify
It's Time To Stop Using Lambda Architecture | Yaroslav Tkachenko, Shopify
 
Bringing Streaming Data To The Masses: Lowering The “Cost Of Admission” For Y...
Bringing Streaming Data To The Masses: Lowering The “Cost Of Admission” For Y...Bringing Streaming Data To The Masses: Lowering The “Cost Of Admission” For Y...
Bringing Streaming Data To The Masses: Lowering The “Cost Of Admission” For Y...
 
5 lessons learned for successful migration to Confluent cloud | Natan Silinit...
5 lessons learned for successful migration to Confluent cloud | Natan Silinit...5 lessons learned for successful migration to Confluent cloud | Natan Silinit...
5 lessons learned for successful migration to Confluent cloud | Natan Silinit...
 
How Much Can You Connect? | Bhavesh Raheja, Disney + Hotstar
How Much Can You Connect? | Bhavesh Raheja, Disney + HotstarHow Much Can You Connect? | Bhavesh Raheja, Disney + Hotstar
How Much Can You Connect? | Bhavesh Raheja, Disney + Hotstar
 
Kafka Summit NYC 2017 - Simplifying Omni-Channel Retail at Scale
Kafka Summit NYC 2017 - Simplifying Omni-Channel Retail at ScaleKafka Summit NYC 2017 - Simplifying Omni-Channel Retail at Scale
Kafka Summit NYC 2017 - Simplifying Omni-Channel Retail at Scale
 
Bank of China Tech Talk 2: Introduction to Streaming Data and Stream Processi...
Bank of China Tech Talk 2: Introduction to Streaming Data and Stream Processi...Bank of China Tech Talk 2: Introduction to Streaming Data and Stream Processi...
Bank of China Tech Talk 2: Introduction to Streaming Data and Stream Processi...
 
Building Event-Driven Microservices using Kafka Streams (Stathis Souris, Thou...
Building Event-Driven Microservices using Kafka Streams (Stathis Souris, Thou...Building Event-Driven Microservices using Kafka Streams (Stathis Souris, Thou...
Building Event-Driven Microservices using Kafka Streams (Stathis Souris, Thou...
 
Low-latency real-time data processing at giga-scale with Kafka | John DesJard...
Low-latency real-time data processing at giga-scale with Kafka | John DesJard...Low-latency real-time data processing at giga-scale with Kafka | John DesJard...
Low-latency real-time data processing at giga-scale with Kafka | John DesJard...
 
MongoDB Breakfast Milan - Mainframe Offloading Strategies
MongoDB Breakfast Milan -  Mainframe Offloading StrategiesMongoDB Breakfast Milan -  Mainframe Offloading Strategies
MongoDB Breakfast Milan - Mainframe Offloading Strategies
 
Serverless Architectures with AWS Lambda and MongoDB Atlas by Sig Narvaez
Serverless Architectures with AWS Lambda and MongoDB Atlas by Sig NarvaezServerless Architectures with AWS Lambda and MongoDB Atlas by Sig Narvaez
Serverless Architectures with AWS Lambda and MongoDB Atlas by Sig Narvaez
 
Kafka Summit SF 2017 - Database Streaming at WePay
Kafka Summit SF 2017 - Database Streaming at WePayKafka Summit SF 2017 - Database Streaming at WePay
Kafka Summit SF 2017 - Database Streaming at WePay
 

Similar a Billions of Messages in Real Time: Why Paypal & LinkedIn Trust an Engagement Database

Similar a Billions of Messages in Real Time: Why Paypal & LinkedIn Trust an Engagement Database (20)

Microsoft Azure Explained - Hitesh D Kesharia
Microsoft Azure Explained - Hitesh D KeshariaMicrosoft Azure Explained - Hitesh D Kesharia
Microsoft Azure Explained - Hitesh D Kesharia
 
How Enterprises are Using NoSQL for Mission-Critical Applications
How Enterprises are Using NoSQL for Mission-Critical ApplicationsHow Enterprises are Using NoSQL for Mission-Critical Applications
How Enterprises are Using NoSQL for Mission-Critical Applications
 
Top 10 Enterprise Use Cases for NoSQL
Top 10 Enterprise Use Cases for NoSQLTop 10 Enterprise Use Cases for NoSQL
Top 10 Enterprise Use Cases for NoSQL
 
Microsoft Azure
Microsoft AzureMicrosoft Azure
Microsoft Azure
 
Revolutionizing the customer experience - Hello Engagement Database
Revolutionizing the customer experience - Hello Engagement DatabaseRevolutionizing the customer experience - Hello Engagement Database
Revolutionizing the customer experience - Hello Engagement Database
 
Couchbase and Apache Kafka - Bridging the gap between RDBMS and NoSQL
Couchbase and Apache Kafka - Bridging the gap between RDBMS and NoSQLCouchbase and Apache Kafka - Bridging the gap between RDBMS and NoSQL
Couchbase and Apache Kafka - Bridging the gap between RDBMS and NoSQL
 
Amazon AWS vs Azure Cloud vs Kubernetes
Amazon AWS vs Azure Cloud vs KubernetesAmazon AWS vs Azure Cloud vs Kubernetes
Amazon AWS vs Azure Cloud vs Kubernetes
 
Couchbase Mobile on Android
Couchbase Mobile on AndroidCouchbase Mobile on Android
Couchbase Mobile on Android
 
Webinar - Delivering Enhanced Message Processing at Scale With an Always-on D...
Webinar - Delivering Enhanced Message Processing at Scale With an Always-on D...Webinar - Delivering Enhanced Message Processing at Scale With an Always-on D...
Webinar - Delivering Enhanced Message Processing at Scale With an Always-on D...
 
Real-time Data Streaming from Oracle to Apache Kafka
Real-time Data Streaming from Oracle to Apache Kafka Real-time Data Streaming from Oracle to Apache Kafka
Real-time Data Streaming from Oracle to Apache Kafka
 
Simplifying Big Data Integration with Syncsort DMX and DMX-h
Simplifying Big Data Integration with Syncsort DMX and DMX-hSimplifying Big Data Integration with Syncsort DMX and DMX-h
Simplifying Big Data Integration with Syncsort DMX and DMX-h
 
Streaming Time Series Data With Kenny Gorman and Elena Cuevas | Current 2022
Streaming Time Series Data With Kenny Gorman and Elena Cuevas | Current 2022Streaming Time Series Data With Kenny Gorman and Elena Cuevas | Current 2022
Streaming Time Series Data With Kenny Gorman and Elena Cuevas | Current 2022
 
Ibm integrated analytics system
Ibm integrated analytics systemIbm integrated analytics system
Ibm integrated analytics system
 
Couchbase Chennai Meetup 2 - Big Data & Analytics
Couchbase Chennai Meetup 2 - Big Data & AnalyticsCouchbase Chennai Meetup 2 - Big Data & Analytics
Couchbase Chennai Meetup 2 - Big Data & Analytics
 
How leading financial services organisations are winning with tech
How leading financial services organisations are winning with techHow leading financial services organisations are winning with tech
How leading financial services organisations are winning with tech
 
Couchbase Cloud No Equal (Rick Jacobs, Couchbase) Kafka Summit 2020
Couchbase Cloud No Equal (Rick Jacobs, Couchbase) Kafka Summit 2020Couchbase Cloud No Equal (Rick Jacobs, Couchbase) Kafka Summit 2020
Couchbase Cloud No Equal (Rick Jacobs, Couchbase) Kafka Summit 2020
 
Benefits of the Azure cloud
Benefits of the Azure cloudBenefits of the Azure cloud
Benefits of the Azure cloud
 
How the Development Bank of Singapore solves on-prem compute capacity challen...
How the Development Bank of Singapore solves on-prem compute capacity challen...How the Development Bank of Singapore solves on-prem compute capacity challen...
How the Development Bank of Singapore solves on-prem compute capacity challen...
 
Cortana Analytics Workshop: The "Big Data" of the Cortana Analytics Suite, Pa...
Cortana Analytics Workshop: The "Big Data" of the Cortana Analytics Suite, Pa...Cortana Analytics Workshop: The "Big Data" of the Cortana Analytics Suite, Pa...
Cortana Analytics Workshop: The "Big Data" of the Cortana Analytics Suite, Pa...
 
Enterprise Architecture vs. Data Architecture
Enterprise Architecture vs. Data ArchitectureEnterprise Architecture vs. Data Architecture
Enterprise Architecture vs. Data Architecture
 

Más de confluent

Más de confluent (20)

Catch the Wave: SAP Event-Driven and Data Streaming for the Intelligence Ente...
Catch the Wave: SAP Event-Driven and Data Streaming for the Intelligence Ente...Catch the Wave: SAP Event-Driven and Data Streaming for the Intelligence Ente...
Catch the Wave: SAP Event-Driven and Data Streaming for the Intelligence Ente...
 
Santander Stream Processing with Apache Flink
Santander Stream Processing with Apache FlinkSantander Stream Processing with Apache Flink
Santander Stream Processing with Apache Flink
 
Unlocking the Power of IoT: A comprehensive approach to real-time insights
Unlocking the Power of IoT: A comprehensive approach to real-time insightsUnlocking the Power of IoT: A comprehensive approach to real-time insights
Unlocking the Power of IoT: A comprehensive approach to real-time insights
 
Workshop híbrido: Stream Processing con Flink
Workshop híbrido: Stream Processing con FlinkWorkshop híbrido: Stream Processing con Flink
Workshop híbrido: Stream Processing con Flink
 
Industry 4.0: Building the Unified Namespace with Confluent, HiveMQ and Spark...
Industry 4.0: Building the Unified Namespace with Confluent, HiveMQ and Spark...Industry 4.0: Building the Unified Namespace with Confluent, HiveMQ and Spark...
Industry 4.0: Building the Unified Namespace with Confluent, HiveMQ and Spark...
 
AWS Immersion Day Mapfre - Confluent
AWS Immersion Day Mapfre   -   ConfluentAWS Immersion Day Mapfre   -   Confluent
AWS Immersion Day Mapfre - Confluent
 
Eventos y Microservicios - Santander TechTalk
Eventos y Microservicios - Santander TechTalkEventos y Microservicios - Santander TechTalk
Eventos y Microservicios - Santander TechTalk
 
Q&A with Confluent Experts: Navigating Networking in Confluent Cloud
Q&A with Confluent Experts: Navigating Networking in Confluent CloudQ&A with Confluent Experts: Navigating Networking in Confluent Cloud
Q&A with Confluent Experts: Navigating Networking in Confluent Cloud
 
Citi TechTalk Session 2: Kafka Deep Dive
Citi TechTalk Session 2: Kafka Deep DiveCiti TechTalk Session 2: Kafka Deep Dive
Citi TechTalk Session 2: Kafka Deep Dive
 
Build real-time streaming data pipelines to AWS with Confluent
Build real-time streaming data pipelines to AWS with ConfluentBuild real-time streaming data pipelines to AWS with Confluent
Build real-time streaming data pipelines to AWS with Confluent
 
Q&A with Confluent Professional Services: Confluent Service Mesh
Q&A with Confluent Professional Services: Confluent Service MeshQ&A with Confluent Professional Services: Confluent Service Mesh
Q&A with Confluent Professional Services: Confluent Service Mesh
 
Citi Tech Talk: Event Driven Kafka Microservices
Citi Tech Talk: Event Driven Kafka MicroservicesCiti Tech Talk: Event Driven Kafka Microservices
Citi Tech Talk: Event Driven Kafka Microservices
 
Confluent & GSI Webinars series - Session 3
Confluent & GSI Webinars series - Session 3Confluent & GSI Webinars series - Session 3
Confluent & GSI Webinars series - Session 3
 
Citi Tech Talk: Messaging Modernization
Citi Tech Talk: Messaging ModernizationCiti Tech Talk: Messaging Modernization
Citi Tech Talk: Messaging Modernization
 
Citi Tech Talk: Data Governance for streaming and real time data
Citi Tech Talk: Data Governance for streaming and real time dataCiti Tech Talk: Data Governance for streaming and real time data
Citi Tech Talk: Data Governance for streaming and real time data
 
Confluent & GSI Webinars series: Session 2
Confluent & GSI Webinars series: Session 2Confluent & GSI Webinars series: Session 2
Confluent & GSI Webinars series: Session 2
 
Data In Motion Paris 2023
Data In Motion Paris 2023Data In Motion Paris 2023
Data In Motion Paris 2023
 
Confluent Partner Tech Talk with Synthesis
Confluent Partner Tech Talk with SynthesisConfluent Partner Tech Talk with Synthesis
Confluent Partner Tech Talk with Synthesis
 
The Future of Application Development - API Days - Melbourne 2023
The Future of Application Development - API Days - Melbourne 2023The Future of Application Development - API Days - Melbourne 2023
The Future of Application Development - API Days - Melbourne 2023
 
The Playful Bond Between REST And Data Streams
The Playful Bond Between REST And Data StreamsThe Playful Bond Between REST And Data Streams
The Playful Bond Between REST And Data Streams
 

Último

Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Victor Rentea
 

Último (20)

CNIC Information System with Pakdata Cf In Pakistan
CNIC Information System with Pakdata Cf In PakistanCNIC Information System with Pakdata Cf In Pakistan
CNIC Information System with Pakdata Cf In Pakistan
 
WSO2's API Vision: Unifying Control, Empowering Developers
WSO2's API Vision: Unifying Control, Empowering DevelopersWSO2's API Vision: Unifying Control, Empowering Developers
WSO2's API Vision: Unifying Control, Empowering Developers
 
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data DiscoveryTrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
 
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
 
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdf
 
presentation ICT roal in 21st century education
presentation ICT roal in 21st century educationpresentation ICT roal in 21st century education
presentation ICT roal in 21st century education
 
FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024
 
MS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectorsMS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectors
 
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
 
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
 
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
 
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
 
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
 
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost SavingRepurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
 
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWEREMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
 
DEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
DEV meet-up UiPath Document Understanding May 7 2024 AmsterdamDEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
DEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
 
Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...
 
Six Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal OntologySix Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal Ontology
 
AWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of TerraformAWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of Terraform
 
Exploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with MilvusExploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with Milvus
 

Billions of Messages in Real Time: Why Paypal & LinkedIn Trust an Engagement Database

  • 1. Confidential and Proprietary. Do not distribute without Couchbase consent. © Couchbase 2017. All rights reserved. Milliarden von Messages in Echtzeit: Warum Paypal & LinkedIn auf eine Engagement-Datenbank vertrauen 09.10.2018 Bruno Šimić – Solutions Engineer
  • 2. ATTRIBUTES OF AN ENGAGEMENT DATABASE Always on, always fast Secure, secure, secure Built-in smarts Seamlessly mobile Hello cloud, hello world Built for change - at scale
  • 3. Why Customers Choose Couchbase? Memory-first Architecture Full SQL Query Language Active-Active Global Data Replication Multi-dimensional scaling Mobile Confidential and Proprietary. Do not distribute without Couchbase consent. © Couchbase 2018. All rights reserved.
  • 4. Core Principles of Couchbase Platform Evolution Started with Core Principles – True auto sharding – JSON-based flexible data model – Memory-first Architecture – Asynchronous approach to everything – Scale workloads independently Managed Cache Key-Value Store Document Database Mobile N1QL Query Full Text Search Analytics Confidential and Proprietary. Do not distribute without Couchbase consent. © Couchbase 2017. All rights reserved.
  • 5. Confidential and Proprietary. Do not distribute without Couchbase consent. © Couchbase 2018. All rights reserved. 6Confidential and Proprietary. Do not distribute without Couchbase consent. © Couchbase 2018. All rights reserved. Couchbase Hybrid / Multi-Cloud Data Platform • Service-Centric Clustered Data System - Multi-process Architecture - Dynamic Distribution of Facilities - Cluster Map Distribution - Automatic Failover • Offline Mobile Data Integration • N1QL - SQL-like Query Engine for JSON • Global Secondary Indexes • Lowest Latency Key-Value API • Active-Active Inter-DC Replication • Full-Text Search • Eventing • Operational Analytics On-premPrivate Cloud AWSAzure GCP Eventing Mobile Query Key Value Analytics Indexing Full Text Search
  • 6. Couchbase designed for containerized applications
  • 7. Introducing Couchbase Autonomous Operator Couchbase Autonomous Operator is an application-specific controller that extends the Kubernetes API to create, configure and manage instances of complex stateful applications on behalf of a Kubernetes user. It builds upon the basic Kubernetes resource and controller concepts, but also includes domain or application-specific knowledge to automate common tasks better managed by computers.
  • 8. Couchbase K8 operator Architecture
  • 9. Next Generation Data Management Architecture Data Sources Enterprise Applications Social Media Web & Ecommerce Mobile AppsSensor Data MainframeExternal DataSystem Logs Data Integration Speed Layer Batch Layer Data Management Data Lake Data Warehouse Business Intelligence Dashboards Query ToolsData Access In Memory Cache Data Serving Layer
  • 10. Next Generation Data Management Architecture Enterprise Applications Social Media Web & Ecommerce Mobile AppsSensor Data MainframeExternal DataSystem Logs Speed Layer Batch Layer Data Lake Business Intelligence Dashboards Query Tools In Memory Cache Data Warehouse N1QL Query Workbench Data Sources Data Integration Data Management Data Access Data Serving Layer Real Time Data Ingestion
  • 11. Ingest, Process, Load and Serve Data at global scale Confidential and Proprietary. Do not distribute without Couchbase consent. © Couchbase 2018. All rights reserved.
  • 12. Kafka Connect Couchbase Connector 3.4 Confidential and Proprietary. Do not distribute without Couchbase consent. © Couchbase 2018. All rights reserved. • Use Couchbase as either a consumer or producer with Kafka message queues • Continuous streaming, filter, and transformation of events to and from Couchbase with Source and Sink connectors. • Fast, reliable and fault tolerant: Based on DCP (Couchbase replication protocol). • Efficient: Only load new or modified documents. • Real-time: Every mutation to Couchbase generates an event which is published to a Kafka topic. • Compression and IPv6 support • Support for rollback mitigation Couchbase cluster … Kafka cluster Kafka Connect (Connectors to Extract and Load data)
  • 13. Confluent and Couchbase - Synergies Confidential and Proprietary. Do not distribute without Couchbase consent. © Couchbase 2018. All rights reserved. • Distributed and fault tolerant • Horizontally scalable • Geographically replicated • Low latency • Open source
  • 14. Customer Spotlight 1.1 trillion hits a day 75% of flight bookings worldwide are made through Amadeus 50M Unique monthly visitors 2.5B monthly page views Replaced MongoDB 2821 nodes, 100+ clusters 16M entries every 5 min 2.5 millon ops/sec. on a single cluster 1 billion+ documents 10TB+ data Sub-2oo ms response time E-Commerce Travel CommunicationsGaming Financial Services Health Industrial IoTDigital Media
  • 15. 17 Objectives & Challenges Provide business users with real time reports and visualizations of user interaction data • Collect web and mobile clickstream in real time • Integrate with other big data technologies (Hadoop and Storm) • Provide views of data across multiple dimensions (e.g., time, location, browser and device types) Solution Deploy Couchbase Server to capture, store, and process real time web data • Ingests data (via Storm) from multiple inputs, including mobile, web, and other services, storing data as JSON documents • Integrates with Hadoop to pass data for additional offline analytics • 130m+ active accounts, in 190+ countries, 25 currencies • 10TB data • 1B documents The Couchbase Advantage Real time performance, easy integration with Kafka, Storm and Hadoop Confidential and Proprietary. Do not distribute without Couchbase consent. © Couchbase 2018. All rights reserved. User Activity Tracking and real-time analytics @ Paypal Results • Consistent low latency (sub 10-msec response) • High availability enabled by distributed caching and XDCR • Views for business users are generated in under 1 minute, based on 10-minute data collection intervals
  • 16. 17 Objectives & Challenges Read scaling and TCO becomes important • Constant growth of user profiles, groups, jobs and publications • Difficult to move data across data centers • Very complex administration of the system • Risk of security breach by using many different components Solution Deploy Couchbase Server to cache, store and replicate data in real time with low latency • One singe solution for in memory caching, ephemeral counter store, temporary de-duping store and SoT for internal tooling • Center of excellence for Couchbase within Linkedin created • LinkedIn build ist own NoSQL databas (Voldemort), Couchbase is still used as the main database for this use cases • 560M users, 26M companies, 15M active jobs listings • 1.5B documents in cluster • 10M queries/sec • 30 Offices in 24 countries • 24 languages Confidential and Proprietary. Do not distribute without Couchbase consent. © Couchbase 2018. All rights reserved. Read scaling & data replication across DCs worldwide Results • Consistent low latency • High availability enabled by distributed caching and XDCR • Higher acceptance at users • Scalable and performant system with zero downtime • Lower TCO
  • 17. Additional information Confidential and Proprietary. Do not distribute without Couchbase consent. © Couchbase 2018. All rights reserved.
  • 18. Couchbase Mobile: The Full-Stack Mobile Data Platform Confidential and Proprietary. Do not distribute without Couchbase consent. © Couchbase 2018. All rights reserved. Lightweight embedded NoSQL database with full CRUD and query functionality. Secure web gateway with synchronization, data access, and data integration APIs for accessing, integrating, and synchronizing data over the web. Highly scalable, highly available, high performance NoSQL database server. Built-in enterprise level security throughout the entire stack includes user authentication, user and role based data access control (RBAC), secure transport (TLS), and 256-bit AES full database encryption. Couchbase Lite Sync Gateway Couchbase Cluster SECURITY EMBEDDED DATABASE SYNCHRONIZATION DATABASE SERVERCLIENT WEB TIER DATABASEinternet intranet
  • 19. Developing with Couchbase Confidential and Proprietary. Do not distribute without Couchbase consent. © Couchbase 2018. All rights reserved. Couchbase supports a wide range of frameworks, languages, platforms and infrastructure choices. FRAMEWORKS LANGUAGES PLATFORMS INFRASTRUCTURE MOBILEMOBILE
  • 20. Services & Training geared to customer success 2 3 Professional Services • Center of Excellence with product experts • Packaged Services • Workshops • Custom Consulting • Comprehensive NoSQL & Couchbase training • Hands-on, intensive labs • Best practices based on 100s of real use cases • Developer and Admin courses • Global Couchbase facilities, or at customer site Learning Services Email inquiries: Services@couchbase.com Visit us: http://www.couchbase.com/couchbase-services Email inquiries: Training@couchbase.com Visit us: http://training.couchbase.com
  • 21. Additional Resources • Kafka connector: https://docs.couchbase.com/kafka- connector/3.4/index.html • Blog: http://blog.couchbase.com • Forum: http://forums.couchbase.com • General Docs: http://docs.couchbase.com • Developer Portal: http://developer.couchbase.com • Couchbase Labs: https://github.com/couchbaselabs • Query Portal: http://query.couchbase.com Confidential and Proprietary. Do not distribute without Couchbase consent. © Couchbase 2018. All rights reserved.