– For web applications and cloud computing environments – Most mature, reliable and widely deployed NoSQL database solution – Fully featured, open source document datastore – Headquartered in Silicon Valley – Couchbase team has authored majority of memcached and CouchDB codebase Wednesday, November 9, 11
(iPhone and Android) Couchbase Single Server (Single Node) Most full featured Document Database Couchbase Server (Multi-Node) Simple, Fast, Elastic NoSQL Datastore Wednesday, November 9, 11
featured Document Database CouchSync CouchSync Couchbase Mobile (iPhone and Android) Couchbase Server (Multi-Node) Simple, Fast, Elastic NoSQL Datastore Wednesday, November 9, 11
for 40 years, and will likely continue to do so for the foreseeable future to support transactions requiring ACID guarantees. But a large, and increasingly dominant, class of software systems and data do not need those guarantees. Much of the data manipulated by Web applications have less strict transactional requirements but, for lack of a practical alternative, many IT teams continue to use relational technology, needlessly tolerating its cost and scalability limitations. For these applications and data, distributed document cache and database technologies such as Couchbase’s provide a promising alternative. Carl Olofson IDC Research Vice President, Information and Data Management “ ” Wednesday, November 9, 11
more commodity web servers Database Scales Up Get a bigger, more complex server -Expensive and disruptive sharding -Doesn’t perform at Web Scale Wednesday, November 9, 11
Was thousands, now often millions or more • Amount of data stored in apps growing rapidly – Was GBs, now often 1000s of GBs or more • Types of data stored in apps is different – Was structured, now often unstructured & user- generated – Many apps including social features to increase engagement • Data you want to store is changing rapidly – Fixed data model was okay, now its not flexible enough • High-speed networking is inexpensive Things Have Changed Wednesday, November 9, 11
Out Just add more commodity web servers Database Scales Out Just add more commodity data servers Scaling out flattens the cost and performance curves. • Horizontally scalable with auto- sharding • High performance at web scale • Schema-less for flexibility Wednesday, November 9, 11
documentation and resources available • Worldwide training events and meet up groups • CouchConf – User Conference in San Francisco and other major cities Wednesday, November 9, 11
Open source build – Free forum support • Enterprise Edition – Free for non-production use – Certified, QA tested version of open source – Case tracking and guaranteed SLA for production environments – Annual subscriptions starting at $999/node – Hourly cloud pricing via RightScale Wednesday, November 9, 11
Managed memory caching layer = super high performance • Clustering and online data redistribution (Rebalancing) • Indexing and Querying via JSON Map-Reduce • New SDK’s and client libraries • Developer Preview available today! • http://www.couchbase.com/downloads = Simple. Fast. Elastic. Wednesday, November 9, 11
supervisor Configuration manager on each node Rebalance orchestrator Node health monitor one per cluster vBucket state and replication manager http REST management API/Web UI Erlang/OTP Cluster Manager Database Operations Cluster Management storage interface Couch API Membase EP Engine Moxi Data Manager Wednesday, November 9, 11
manager on each node Rebalance orchestrator Node health monitor one per cluster vBucket state and replication manager http REST management API/Web UI 5984 Couch View CouchDB Memcached Couchbase Server 2.0 Architecture Couch API Membase EP Engine 11210 Memcapable 2.0 Moxi 11211 Memcapable 1.0 HTTP 8091 Erlang port mapper 4369 Distributed Erlang 21100 - 21199 Membase Erlang/OTP Wednesday, November 9, 11
server Listener-Sender Master server for KEY Replica Server 2 for KEY Replica Server 1 for KEY 3 3 1 SET acknowledgement returned to application 2 Disk Disk Disk RAM Couchbase storage engine Disk Disk Disk 4 Wednesday, November 9, 11
SDK Ruby SDK Python SDK spymemcached Connection HTTP couchDB connection Java client API User Code Couchbase Server CouchbaseClient cb = new CouchbaseClient(listURIs, "aBucket", "letmein"); // this is all the same as before cb.set("hello", 0, "world"); cb.get("hello"); Map<String, Object> manyThings = cb.getBulk(Collection<String> keys); /* accessing a view View view = cb.getView("design_document", "my_view"); Query query = new Query(); query.getRange("abegin", "theend"); http://www.couchbase.org/code Wednesday, November 9, 11
Each server stores both active & replica docs Only one server active at a time Basic Operation Doc 2 Doc 5 SERVER 1 Doc 4 SERVER 2 Doc 1 SERVER 3 Doc 9 Doc 7 Doc 8 Doc 6 Doc 3 DOC DOC DOC DOC DOC DOC DOC DOC DOC Active Docs Active Docs Active Docs COUCHBASE SERVER CLUSTER Wednesday, November 9, 11
Each server stores both active & replica docs Only one server active at a time Client library provides app with simple interface to database Basic Operation Doc 2 Doc 5 SERVER 1 Doc 4 SERVER 2 Doc 1 SERVER 3 Doc 9 Doc 7 Doc 8 Doc 6 Doc 3 DOC DOC DOC DOC DOC DOC DOC DOC DOC Active Docs Active Docs Active Docs COUCHBASE SERVER CLUSTER Wednesday, November 9, 11
Each server stores both active & replica docs Only one server active at a time Client library provides app with simple interface to database Cluster map provides map to which server doc is on App never needs to know Basic Operation Doc 2 Doc 5 SERVER 1 Doc 4 SERVER 2 Doc 1 SERVER 3 Doc 9 Doc 7 Doc 8 Doc 6 Doc 3 DOC DOC DOC DOC DOC DOC DOC DOC DOC Active Docs Active Docs Active Docs COUCHBASE SERVER CLUSTER Wednesday, November 9, 11
Each server stores both active & replica docs Only one server active at a time Client library provides app with simple interface to database Cluster map provides map to which server doc is on App never needs to know App reads, writes, updates docs Basic Operation Doc 2 Doc 5 SERVER 1 Doc 4 SERVER 2 Doc 1 SERVER 3 Doc 9 Doc 7 Doc 8 Doc 6 Doc 3 DOC DOC DOC DOC DOC DOC DOC DOC DOC Active Docs Active Docs Active Docs COUCHBASE SERVER CLUSTER Wednesday, November 9, 11
Each server stores both active & replica docs Only one server active at a time Client library provides app with simple interface to database Cluster map provides map to which server doc is on App never needs to know App reads, writes, updates docs Multiple App Servers can access same document at same time Basic Operation Doc 2 Doc 5 SERVER 1 Doc 4 SERVER 2 Doc 1 SERVER 3 Doc 9 Doc 7 Doc 8 Doc 6 Doc 3 DOC DOC DOC DOC DOC DOC DOC DOC DOC Active Docs Active Docs Active Docs COUCHBASE SERVER CLUSTER Wednesday, November 9, 11
Each server stores both active & replica docs Only one server active at a time Client library provides app with simple interface to database Cluster map provides map to which server doc is on App never needs to know App reads, writes, updates docs Multiple App Servers can access same document at same time Basic Operation Doc 4 Doc 2 Doc 5 SERVER 1 Doc 6 Doc 4 SERVER 2 Doc 7 Doc 1 SERVER 3 Doc 3 User Configured Replica Count = 1 Doc 9 Doc 7 Doc 8 Doc 6 Doc 3 DOC DOC DOC DOC DOC DOC DOC DOC DOC DOC DOC DOC DOC DOC DOC Doc 9 Doc 5 DOC DOC DOC Doc 1 Doc 8 Doc 2 Replica Docs Replica Docs Replica Docs Active Docs Active Docs Active Docs COUCHBASE SERVER CLUSTER Wednesday, November 9, 11
in the cluster Each server stores both active & replica docs Only one server active at a time Client library provides app with simple interface to database Cluster map provides map to which server doc is on App never needs to know App reads, writes, updates docs Multiple App Servers can access same document at same time Basic Operation Doc 4 Doc 2 Doc 5 SERVER 1 Doc 6 Doc 4 SERVER 2 Doc 7 Doc 1 SERVER 3 Doc 3 User Configured Replica Count = 1 COUCHBASE CLIENT LIBRARY Doc 9 Doc 7 Doc 8 Doc 6 Doc 3 DOC DOC DOC DOC DOC DOC DOC DOC DOC DOC DOC DOC DOC DOC DOC Doc 9 Doc 5 DOC DOC DOC Doc 1 Doc 8 Doc 2 Replica Docs Replica Docs Replica Docs Active Docs Active Docs Active Docs CLUSTER MAP CLUSTER MAP APP SERVER 1 APP SERVER 2 COUCHBASE SERVER CLUSTER Wednesday, November 9, 11
in the cluster Each server stores both active & replica docs Only one server active at a time Client library provides app with simple interface to database Cluster map provides map to which server doc is on App never needs to know App reads, writes, updates docs Multiple App Servers can access same document at same time Basic Operation Doc 4 Doc 2 Doc 5 SERVER 1 Doc 6 Doc 4 SERVER 2 Doc 7 Doc 1 SERVER 3 Doc 3 User Configured Replica Count = 1 Read/Write/Update COUCHBASE CLIENT LIBRARY Read/Write/Update Doc 9 Doc 7 Doc 8 Doc 6 Doc 3 DOC DOC DOC DOC DOC DOC DOC DOC DOC DOC DOC DOC DOC DOC DOC Doc 9 Doc 5 DOC DOC DOC Doc 1 Doc 8 Doc 2 Replica Docs Replica Docs Replica Docs Active Docs Active Docs Active Docs CLUSTER MAP CLUSTER MAP APP SERVER 1 APP SERVER 2 COUCHBASE SERVER CLUSTER Wednesday, November 9, 11
locations for disaster recovery Can write to same document in all different regions & it will sync Cross Data Center Replication US DATA CENTER EUROPE DATA CENTER ASIA DATA CENTER CouchSync CouchSync CouchSync Wednesday, November 9, 11
data from Couchbase to Hadoop – Real-time integration using Flume – Batch integration using Sqoop • Examples – Various game statistics (e.g., monthly / daily / hourly rankings) – Analyze game patterns from users to enhance various game metrics Couchbase and Hadoop Integration memcached protocol listener/sender engine interface Couchbase Storage Engine TAP Flume Sqoop Wednesday, November 9, 11
available offline • Real-time multi- device synchronization • Including to the Cloud • iOS and Android support • SDKs provided (CouchCocoa, Ektorp) Check it out today at: http:// www.couchbase.org/get/couchbase-mobile- for-ios/current Wednesday, November 9, 11
cloud service (PAAS) provider • Over 65,000 hosted applications • Membase Server serving over • Social game leader – FarmVille, Mafia Wars, Café World • Over 230 million monthly users • Membase Server is the primary database behind key Zynga properties Wednesday, November 9, 11
-Multiple Couchbase servers under moderate load (10k-15k operations per second) -Dynamic scalability – adding nodes on the fly -Secondary indices – Generation, querying, updating Take-away? Wednesday, November 9, 11
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