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Moving Beyond SQL – Delivering Personalized, Responsive Experiences that Customers Crave

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The applications that today’s enterprises are building require flexibility, performance and scalability, and agnostic deployment options to meet the demands of business, employee, and customer. If you’re an architect or developer, you know building a great-looking app is just the beginning.

Liberating data fast and at scale is what allows you to deliver a seamless application experience every time – regardless of device, location, or time. But traditional relational databases weren’t built to meet the quickly changing requirements of modern web, mobile, and IoT apps, to deliver personalized and responsive digital experiences.

What’s the answer? A NoSQL datastore may help achieve these goals – but there are several factors to consider. Not all NoSQL engines are built on the same principles, so what do people need to know when evaluating NoSQL options?

In this webinar, we’ll share real-world lessons learned from customers, and practical advice and best practices for defining, choosing and then moving applications from a traditional RDBMS to NoSQL including:

How application needs are evolving in the world of digital
When to consider NoSQL vs a traditional RDBMS -Pros and cons of different NoSQL architectures
When to use a document-centric option like Couchbase
How to bridge the gap between NoSQL and SQL
If you are facing the data infrastructure bottlenecks caused by traditional database architectures, or you are just getting started and want learn from what others are doing, join us to learn about moving beyond SQL

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Moving Beyond SQL – Delivering Personalized, Responsive Experiences that Customers Crave

  1. 1. Confidential and Proprietary. Do not distribute without Couchbase consent. © Couchbase 2017. All rights reserved. MOVING BEYOND SQL Addressing the challenges of RDBMS technology Tyler Mitchell | Senior Product Marketing Manager Nov 2018
  2. 2. Confidential and Proprietary. Do not distribute without Couchbase consent. © Couchbase 2017. All rights reserved. MOVING BEYOND SQL RELATIONAL Addressing the challenges of RDBMS technology Tyler Mitchell | Senior Product Marketing Manager Nov 2018
  3. 3. AGENDA 1. What is Couchbase? 2. Challenges of RDBMS 3. Making the Move 4. Use Cases 3
  4. 4. Customers spend more time interacting than transacting…
  5. 5. Customers expect exceptional digital experiences Feature-rich Quick Anywhere AnytimePersonalized
  6. 6. The traditional approachWhy today’s digital transformation projects fail Analytical Database Transactional Database
  7. 7. Point solutions everywhereWhy today’s digital transformation projects fail Global Replication Search Key Value Indexing Cache Analytics Mobile Query Transactional Database Analytical Database
  8. 8. Why today's digital transformation projects succeed Transactional Database Analytical Database Bring in the Engagement Database Engagement Database
  9. 9. 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
  10. 10. Couchbase Data Platform • Couchbase delivers the Data Platform for the Digital Economy • Products: Couchbase Server & Couchbase Mobile • Open source NoSQL, JSON document database • Founded 2010 • 500+ enterprise customers, including 20+ Fortune 100
  11. 11. WHY NOT RDBMS?2
  12. 12. Traditional databases hold business back Rigid schemas Inability to scale Performance challenges Cost Confidential and Proprietary. Do not distribute without Couchbase consent. © Couchbase 2017. All rights reserved.
  13. 13. Relational Database Limitations Agility & Flexibility Performance At any Scale Simple Management
  14. 14. Relational Database Limitations Agility & Flexibility RDBMSs don’t handle change well • Applications require constant change to keep pace • There’s little time to wait when new functionality must be delivered • Schema changes are disruptive and time consuming The database must keep pace with – and mirror - the agile development process
  15. 15. Couchbase more Agile and Flexible Agility & Flexibility Couchbase’s JSON data structure = agility! • JSON documents make data manipulation very simple • Much less code is required • Less code = fewer bugs and faster time to market Today’s modern programmers appreciate JSON and are more efficient with it
  16. 16. Relational Database Limitations RDBMS don’t scale linearly • Scale UP vs. OUT means provisioning for peak capacity • Hardware and operational costs quickly get out of control • Not suited to cloud or containers RDBMS cannot embrace modern scalability with commodity computing Relational Database System of Record RDBMS SCALES UP Get a bigger, more expensive server USERS SYSTEM COST APPLICATION PERFORMANCE WON’T SCALE BEYOND A POINT Performance At any Scale
  17. 17. Couchbase better Performance at any Scale Couchbase = predictable performance at scale • Provision and de-provision effortlessly as business conditions dictate • Deliver linear scalability using commodity hardware, cloud or containers • Non-disruptive scaling with online rebalance of data The database becomes a business enabler, not a roadblock COUCHBASE SCALES OUT USERS APPLICATION PERFORMANCE SYSTEM COST Web/App Server Tier Engagement Database Performance At any Scale
  18. 18. Relational Database Limitations Sharding is a massive RDBMS headache • Related to the scale-up problem of RDBMS (monolithic) • Requires constant manual intervention and configuring • Disruptive to 99.999 availability Dramatically increases the operational overhead of the database layer Simple Management
  19. 19. Couchbase easier to Manage Simple Management Couchbase auto-shards by design • Automatic redistribution of data across nodes whenever a new node is added • Replication is built-in • Makes scaling out simple with no application disruption Minimizes operational tasks and costs
  20. 20. MAKING THE MOVE3
  21. 21. Couchbase: The Power of a Flexible JSON Schema Store data in multiple ways: • Denormalized single document • Normalized with references • Add new values when needed • Support for binary values Access Data in multiple ways: • Direct Key-Value • SQL querying • Full-Text Search • MPP for large, ad-hoc access
  22. 22. Data Access: N1QL = SQL for JSON
  23. 23. JOIN in N1QL
  24. 24. Full-Text Search Scoring Document ID Description Matches 1.88 hotel_1234 best location 1.82 hotel_2345 loved hotel location 1.37 hotel_3456 location is awesome 1.25 hotel_4557 hard to locate best hotel location SEARCH Search results • Inverted Index • Term matching • Scoring • Context snippet
  25. 25. Reference Architecture: Start with Caching User Requests Cache Misses and Write Requests RDBMS Application Layer Couchbase Read-Write Requests
  26. 26. Reference Architecture: Replicate Geographically New York London Tokyo Bi-directional XDCR
  27. 27. Reference Architecture: Aggregate other Data Stores Event BusData Sources SUBSCRIBEPUBLISH Ingestion / Enrichment Couchbase Cluster … Couchbase Cluster … Other Data Stores Applications
  28. 28. Reference Architecture: Mobilize Batch Loader Mobile Apps Couchbase Server … Other DBs Sync Gateway Web Apps Change Listener Direct REST COUCHBASE LITE
  29. 29. Confidential and Proprietary. Do not distribute without Couchbase consent. © Couchbase 2017. All rights reserved. USE CASES4
  30. 30. Confidential and Proprietary. Do not distribute without Couchbase consent. © Couchbase 2017. All rights reserved. 30 Couchbase in the Data Management Landscape Enterprise Applications Social Media Web & Ecommerce Mobile Apps Sensor Data Mainframe External Data System Logs Speed Layer Batch Layer Data Lake 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 Business Intelligence
  31. 31. E-Commerce Travel Gaming Communications Financial Services Digital Health Digital Media Industrial IoT Across all Industries
  32. 32. Engagement Use Cases Catalog Metadata Operational Dashboarding User Profile Database Session Database Inventory & Availability Entitlement Management Field Service Enablement Customer 360 Asset/Resource Management Device User Data Management Endpoint Data Management
  33. 33. Customer highlights Catalog Metadata Operational Dashboarding User Profile Database Session Database Inventory & Availability Entitlement Management Field Service Enablement Customer 360 Asset/Resource Management Device User Data Management Endpoint Data Management
  34. 34. Requirements • Inability to scale reads on Oracle was bringing down back-end systems • Memcached caused manageability and reliability problems • Needed to balance performance with built-in replication, cluster expansion, and automatic partitioning to ease load on ops team Outcomes • Achieved tremendous performance at scale, averaging <4ms latency for over 2.5 billion items • LinkedIn standardized on Couchbase, powering 10+ million queries per second across all servers and clusters • Ease of use and built-in replication and cluster expansion have reduced ops costs • World’s largest professional services social network: 450+ million members worldwide • Billions of page hits per day • As user base skyrocketed, quickly outgrew the limited flexibility and scalability of Oracle and turned to NoSQL to run its source of truth (SoT) data store IMPROVING CUSTOMER EXPERIENCE & ENGAGEMENT
  35. 35. Requirements • Growing number of accounts, cards and customers means more data needs to be tracked with sub-ms latency and high throughput • Relational systems unable to scale to the required throughput • HA/DR solutions not streamlined – needed custom development Outcomes • Neural networking algorithms run on Couchbase • Memory-first architecture allows <1ms response times • Complete HA/DR solution delivers 24x365 application uptime • World’s #1 fraud detection platform: scores 65% of world’s credit/debit cards • Couchbase is a profile store, replacing traditional relational database • Each Falcon customer has 100s of millions of card and/or account profiles that can easily be stored and updated based on consumer’s real time activity FASTER INNOVATION & TIME TO MARKET
  36. 36. Requirements • Oracle licensing, hardware, and support costs made scaling difficult • ACID led to performance penalty for key ecommerce app • Needed to increase performance, distribute inventory data geographically and provide high availability Outcomes • Linear scalability paired with very high read/write throughput keep site responsive for users as traffic grows • Location-aware low-latency querying boosts performance • Flexible schema increases developer agility • Active-active bi-directional XDCR keeps site online and available • 4,000 database servers to support 18 million sellers and 164 million active users worldwide • 110 billion Couchbase calls per day • To reduce costs and improve time to market for new features, needed to be able to scale without expanding Oracle environment REDUCE INFRASTRUCTURE & OPERATIONS COSTS
  37. 37. Why Choose Couchbase? Memory-first Architecture Full SQL Query Language Multi-master, Multi-region R/W Multi-dimensional scaling Mobile Cloud/ Container Native
  38. 38. Next Steps Learn More: https://www.couchbase.com/ • Architectural Whitepaper • Relational to NoSQL Whitepaper • Comparing Relational to Couchbase • Performance benchmark comparisons: couchbase.com/benchmarks Free Online Training: https://training.couchbase.com/online Download: https://www.couchbase.com/downloads Contact Us: info@couchbase.com
  39. 39. THANK YOU! 39

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