Couchbase EMEA Q&A Webinar

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Couchbase EMEA Q&A Webinar

  1. 1. Couchbase Q&A Perry Krug Sr. Solutions Architect Simple. Fast. Elastic. 1
  2. 2. Paid Production Deployments (partial list) 2
  3. 3. Couchbase Server (a.k.a. Membase) Simple. Fast. Elastic. NoSQL. Couchbase automatically distributes data across commodity servers. Built-in caching enables apps to read and write data with sub-millisecond latency. And with no schema to manage, Couchbase effortlessly accommodates changing data management requirements. 3
  4. 4. Modern Interactive Software Architecture Application Scales Out Just add more commodity web servers Database Scales Up Get a bigger, more complex server Expensive & disruptive sharding, doesn’t perform at web scale 4
  5. 5. Data Layer Matches Application Logic TierArchitecture Application Scales Out Just add more commodity web servers Database Scales Out Just add more commodity data servers • Horizontally scalable with auto-sharding • High performance at web scale • Schema-less for flexibility Scaling out flattens the cost and performance curves 5
  6. 6. COUCHBASE SOLUTION “THE BASICS” 6
  7. 7. Basic Operation APP SERVER 1 APP SERVER 2  Docs distributed evenly across COUCHBASE CLIENT LIBRARY COUCHBASE CLIENT LIBRARY servers in the cluster  Each server stores both active CLUSTER MAP CLUSTER MAP & replica docs  Only one server active at a time  Client library provides app with Read/Write/Update Read/Write/Update simple interface to database  Cluster map provides map to which server doc is on  App never needs to know SERVER 1 SERVER 2 SERVER 3  App reads, writes, updates Active Docs Active Docs Active Docs docs Doc 5 DOC Doc 4 DOC Doc 1 DOC  Multiple App Servers can Doc 2 DOC Doc 7 DOC Doc 3 DOC access same document at Doc 9 DOC Doc 8 DOC Doc 6 DOC same time Replica Docs Replica Docs Replica Docs Doc 4 DOC Doc 6 DOC Doc 7 DOC Doc 1 DOC Doc 3 DOC Doc 9 DOC Doc 8 DOC Doc 2 DOC Doc 5 DOC COUCHBASE SERVER CLUSTERUser Configured Replica Count = 1 7
  8. 8. Add Nodes APP SERVER 1 APP SERVER 2  Two servers added to COUCHBASE CLIENT LIBRARY COUCHBASE CLIENT LIBRARY cluster  One-click operation CLUSTER MAP CLUSTER MAP  Docs automatically rebalanced across cluster  Even distribution of docs Read/Write/Update Read/Write/Update  Minimum doc movement  Cluster map updated  App database calls now distributed over larger # SERVER 1 SERVER 2 SERVER 3 SERVER 4 SERVER 5 of servers Active Docs Active Docs Active Docs Active Docs Active Docs Active Docs Doc 5 DOC Doc 4 DOC Doc 1 DOC Doc 3 Doc 2 DOC Doc 7 DOC Doc 3 DOC Doc 6 Doc 9 DOC Doc 8 DOC Doc 6 DOC Replica Docs Replica Docs Replica Docs Replica Docs Replica Docs Replica Docs Doc 4 DOC Doc 6 DOC Doc 7 DOC Doc 7 Doc 1 DOC Doc 3 DOC Doc 9 DOC Doc 9 Doc 8 DOC Doc 2 DOC Doc 5 DOC COUCHBASE SERVER CLUSTERUser Configured Replica Count = 1 8
  9. 9. Fail Over Node APP SERVER 1 APP SERVER 2  App servers happily accessing docs on Server 3 COUCHBASE CLIENT LIBRARY COUCHBASE CLIENT LIBRARY  Server fails  App server requests to server 3 fail CLUSTER MAP CLUSTER MAP  Cluster detects server has failed  Promotes replicas of docs to active  Updates cluster map  App server requests for docs now go to appropriate server  Typically rebalance would follow SERVER 1 SERVER 2 SERVER 3 SERVER 4 SERVER 5 Active Docs Active Docs Active Docs Active Docs Active Docs Active Docs Doc 5 DOC Doc 4 DOC Doc 1 DOC Doc 9 DOC Doc 6 DOC Doc 3 Doc 2 DOC Doc 7 DOC Doc 3 Doc 8 DOC Doc 6 DOC Replica Docs Replica Docs Replica Docs Replica Docs Replica Docs Replica Docs Doc 4 DOC Doc 6 DOC Doc 7 DOC Doc 5 DOC Doc 8 DOC Doc 7 Doc 1 DOC Doc 3 DOC Doc 9 DOC Doc 2 DOC Doc 9 COUCHBASE SERVER CLUSTERUser Configured Replica Count = 1 9
  10. 10. PERFORMANCE 10
  11. 11. Your secret weapon: Sub-millisecond AND consistent latencyLatency (micro seconds) Consistently low latencies in microseconds for varying documents sizes with a mixed workload Object size (Bytes) 11
  12. 12. Your secret weapon: Sub-millisecond AND consistent latency High throughput with 1.4 GB/sec data transfer rate using 4 serversOperations per second Linear throughput scalability Number of servers in cluster 12
  13. 13. SCALE 13
  14. 14. Draw Something by OMGPOP 14
  15. 15. As usage grew, game data went non-linear. Draw Something by OMGPOP Daily Active Users (millions) 16 14 12 10 8 By March 19, there were 6 over 30,000,000 downloads of the app, over 5,000 drawings being stored per second, 4 over 2,200,000,000 drawings stored,over 105,000 database transactions per second, Instagram (7.5M in 5 wks) 2 and over 3.3 terabytes of data stored. 2/6 8 10 12 14 16 18 20 22 24 26 28 3/1 3 5 7 9 11 13 15 17 19 21 15
  16. 16. The game exploded. But Couchbase did not. February February February February March March March 6 13 20 27 5 12 19Drawings/second 0 3 50 333 1660 3000 5400 Total drawings 0 5 12 50 500 1 2.2 million million million million billion billion R/W latency (usec) 30 40 32 31 38 29 34 Servers 6 6 6 18 54 72 90 Without a second of downtime, and while sustaining front-end performance, the cluster was continuously expanded to support growth, absorbing frequent server hardware failures. 16
  17. 17. Couchbase Demonstration• Couchbase ServerTemplate Demo – Starting with one database node Application user under load – Dynamically scaling database – Easy management and monitoring Web application server – Not possible any other database technology Couchbase Servers In the EC2 or Datacenter 17
  18. 18. THANK YOU COUCHBASE SIMPLE, FAST, ELASTIC NOSQLHTTP://WWW.COUCHBASE.COM 18

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