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When_Should_I_use_NoSQL_Couchbase_SF_2013
 

When_Should_I_use_NoSQL_Couchbase_SF_2013

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    When_Should_I_use_NoSQL_Couchbase_SF_2013 When_Should_I_use_NoSQL_Couchbase_SF_2013 Presentation Transcript

    • When should I use NoSQL Anil Kumar Technical Product Manager
    • Today’s Agenda  Kinds of Database Management System  When is NoSQL a good fit  Application Requirement-based Use Cases  Common Use Cases
    • Two kinds of Database Management System OLTP / OLTP like Operational Stores Data warehouse or Analytics system
    • Adding a few more components OLTP / OLTP like Operational Stores Analytics Streaming Data ETL RDBMS Data warehouse Other legacy systems RDBMS Column stores Interactive BI & Reporting
    • NoSQL + Big Data Map-reduce against huge datasets to analyze and find insights and answers Operational database for web and mobile apps with high performance at scale
    • Enterprise Architecture Example click stream events profiles, recommendations, etc RDBMS Data Warehouses Reporting and BI
    • Application Requirements-based Use Cases
    • Application Characteristics - Data driven • 3rd party or user defined structure (Twitter feeds) • Support for unlimited data growth (Viral apps) • Data with non-homogenous structure • Need to quickly and often change data structure • Variable length documents • Sparse data records • Hierarchical data NoSQL is a good fit
    • Application Characteristics - Performance driven • Low latency critical (ex. 1millisecond) • High throughput (ex. 200000 ops / sec) • Large number of users • Unknown demand with sudden growth of users/data • Predominantly direct document access • Read / Mixed / Write heavy workloads NoSQL is a good fit
    • Common Use Cases Social Gaming • Couchbase stores player and game data • Examples customers include: Zynga • Tapjoy, Ubisoft, Tencent Mobile Apps • Couchbase stores user info and app content • Examples customers include: Kobo, Playtika Ad Targeting • Couchbase stores user information for fast access • Examples customers include: AOL, Mediamind, Convertro Session store • Couchbase Server as a key- value store • Examples customers include: Concur, Sabre User Profile Store • Couchbase Server as a key-value store • Examples customers include: Tunewiki High availability cache • Couchbase Server used as a cache tier replacement • Examples customers include: Orbitz Content & Metadata Store • Couchbase document store with Elastic Search • Examples customers include: McGraw Hill 3rd party data aggregation • Couchbase stores social media and data feeds • Examples customers include: LivePerson
    • Use Case: High-Availability Caching High availability caching RDBMS Application Layer User Requests Cache Misses and Write Requests Read-Write Requests Couchbase Distributed Cache
    • • Application objects • Popular search query results • Session information • Heavily accessed web landing pages Use Case: High-Availability Caching Data Cached in Couchbase? • Speed up RDBMS • Consistently low response times for document / key lookups • High-availability 24x7x365 • Replacement for entire caching tier Application characteristic
    • Use Case: High-Availability Caching • Low latency in sub-milliseconds with consistently high read / write throughput using built-in cache • Always-on operations even for database upgrades and maintenance with zero down time Why NoSQL?
    • Use Case: Session Store Session Store
    • Use Case: Session Store Data stored in Couchbase? • Extremely fast access to session data using unique session ID • Easy scalability to handle fast growing number of users and user-generated data • Always-on functionality for global user base Application characteristic • Session values or Cookies (stored as key-value pairs) • Examples include: items in a shopping cart, flights selected, search results, etc.
    • Use Case: Session Store • Low latency in sub-milliseconds with consistently high read / write throughput for session data via the built-in object-level cache • Linear throughput scalability to grow the database as user and data volume grow • Always-on operations even particularly high availability using Couchbase replication and failover • Intra cluster and cross cluster (XDCR) replication for globally distributed active-active platform Why NoSQL?
    • Use Case: Globally Distributed User Profile Store User ID / Profile Store
    • Use Case: Globally Distributed User Profile Store Data stored in Couchbase? • Extremely fast access to individual profiles • Always online system as multiple applications access user profiles • Flexibility to add and update user attributes • Easy scalability to handle fast growing number of users Application characteristic • User profile with unique ID • User setting / preferences • User’s network • User application state
    • Use Case: Globally Distributed User Profile Store • Low latency and high throughput for very quick lookups for millions of concurrent users using built-in cache • Intra cluster and cross cluster (XDCR) replication for high availability and disaster recovery • Active-active geo-distributed system to handle globally distributed user base • Online admin operations eliminate system downtime Why NoSQL?
    • Use Case: Data Aggregation Data Aggregation
    • Use Case: Data Aggregation Data stored in Couchbase? • Flexibility to store any kind of content • Flexibility to handle schema changes • Full-text Search across data set • High speed data ingestion • Scales horizontally as more content gets added to the system Application characteristic • Social media feeds: Twitter, Facebook, LinkedIn • Blogs, news, press articles • Data service feeds: Hoovers, Reuters • Data form other systems
    • Use Case: Data Aggregation • JSON provides schema flexibility to store all types of content and metadata • Fast access to individual documents via built-in cache, high write throughput • Indexing and querying provides real-time analytics capabilities across dataset • Integration with ElasticSearch for full-text search • Ease of scalability ensures that the data cluster can be grown seamlessly as the amount of user and ad data grows Why NoSQL?
    • Use Case: Content and Metadata Store Data Aggregation
    • Use Case: Content and Metadata Store Data stored in Couchbase? • Flexibility to store any kind of content • Fast access to content metadata (most accessed objects) and content • Full-text Search across data set • Scales horizontally as more content gets added to the system Application characteristic • Content metadata • Content: Articles, text • Landing pages for website • Digital content: eBooks, magazine, research material
    • Use Case: Content and Metadata Store • Fast access to metadata and content via object-managed cache • JSON provides schema flexibility to store all types of content and metadata • Indexing and querying provides real-time analytics capabilities across dataset • Integration with ElasticSearch for full-text search • Ease of scalability ensures that the data cluster can be grown seamlessly as the amount of user and ad data grows Why NoSQL?
    • McGraw Hill Education Labs Learning portal
    • Use Case: Content and metadata store Building a self-adapting, interactive learning portal with Couchbase
    • As learning move online in great numbers Growing need to build interactive learning environments that Scale! Scale to millions of learners Serve MHE as well as third-party content Including open content Support learning apps 0101001001 1101010101 0101001010 101010 Self-adapt via usage data The Problem
    • • Allow for elastic scaling under spike periods • Ability to catalog & deliver content from many sources • Consistent low-latency for metadata and stats access • Require full-text search support for content discovery • Offer tunable content ranking & recommendation functions Backend is an Interactive Content Delivery Cloud that must: XML Databases SQL/MR Engines In-memory Data Grids Enterprise Search Servers Experimented with a combination of: The Challenge
    • Architecture
    • Questions?
    • Thank you! anil@couchbase.com