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What's New in Couchbase 4.0 – Couchbase Connect 2015

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In this session we will do a lap around the full Couchbase Server 4.0 product. Couchbase VP of Product Management, Chin Hong will explore new capabilities in the latest release including N1QL, Global Secondary Indexing, Multi-Dimensional Scaling and more. In this session, you will: 1) Learn how Couchbase Server 4.0 simplifies querying with N1QL and new global secondary indexing 2) Explore the benefits offered by spatial views 3) Look at how compliance with security rules gets easier and 4) Review architectural advances in ForestDB, Couchbase’s next generation storage engine. This is the grand tour and is the session for you if you want an end-to-end look at all the new capabilities that Couchbase Server 4.0 has to offer.

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What's New in Couchbase 4.0 – Couchbase Connect 2015

  1. 1. WHAT’S NEW IN COUCHBASE SERVER 4.0? Chin Hong VP Product Management, Couchbase
  2. 2. ©2015 Couchbase Inc. 2 Agenda What’s New in Couchbase Server 4.0  Querying with N1QL  Indexing  Multi-Dimensional Scaling  ForestDB: Next-Generation Storage Engine  Security
  3. 3. ©2015 Couchbase Inc. 3 AndThere’s More … Feature Description XDCR Filtering Key-based filtering on XDCR streams addressing reference data & geo-based replication use cases. Bloom Filters Significantly improved latency for low % working set (DGM) situations Memory Defragmentation Use memory according to one’s needs Improved Cluster Robustness Rogue view queries no longer cause cluster manager outage Breakpad Compact and readable crash logs for memcached SDK First class SDK support across Couchbase Server 4.0 features SUSE, Oracle Enterprise Linux, CentOS 7, RHEL 7, Ubuntu 14.04 Expand the supported production platforms
  4. 4. Querying with N1QL
  5. 5. ©2015 Couchbase Inc. 5 What is N1QL? 5 Flexibility of JSONPower of SQL
  6. 6. ©2015 Couchbase Inc. 6 How Does One Evaluate a Query Language? Expressive Declarative Ecosystem
  7. 7. ©2015 Couchbase Inc. 7 N1QL is Expressive: E-Commerce Examples SELECT product.name, SUM(items.count) AS unitsSold FROM purchases UNNEST purchases.lineItems AS items JOIN product ON KEYS items.product GROUP BY product ORDER BY unitsSold DESC LIMIT 10 SELECT SUBSTR(purchases.purchasedAt, 0, 7) AS month, ROUND(SUM(product.unitPrice * items.count)/1000000, 3) revenueMillion FROM purchases UNNEST purchases.lineItems AS items JOIN product ON KEYS items.product GROUP BY SUBSTR(purchases.purchasedAt, 0, 7) ORDER BY month
  8. 8. ©2015 Couchbase Inc. 8 N1QL is Expressive: Image Processing Example SELECT m.image AS gallery_image, s.image AS source_image, s.x, s.y, m.r AS gallery_r, m.g AS gallery_g, m.b AS gallery_b, s.r AS source_r, s.g AS source_g, s.b AS source_b, FROM SourcePixels s JOIN GalleryMeans m ON KEY s.rgb Source: http://www.metanautix.com/tr01 Learn more about N1QL @ query.couchbase.com/tutorial
  9. 9. ©2015 Couchbase Inc. 9 Sessions on N1QL  Introducing N1QL: Query Without Compromise May 3 @ 1:00 pm – 1:45 pm, ArchitectureTrack May 4 @ 11:15 am – 12:00 pm, ArchitectureTrack  N1QL and SDK Support for Java, .NET, and Node.js May 3 @ 4:30 pm - 5:15 pm, Developer Track  Migrating MySQL Queries to N1QL May 4 @ 1:00 am – 1:45 pm, Developer Track  Big Data Query Landscape: N1QL and More May 4 @ 4:30 pm – 5:15 pm, ArchitectureTrack  Interactive Data Analytics with Couchbase N1QL – Nielsen May 3 @ 1:45 pm - 2:30 pm, Developer Track  Agility with Data Modeling at DIRECTV Using N1QL in Couchbase with Node.js - DIRECTV May 4 @ 3:45 pm - 4:30 pm, Developer Track
  10. 10. ©2015 Couchbase Inc. 10 N1QL is Declarative: What vs. How You specify WHAT Couchbase Server figures out HOW
  11. 11. ©2015 Couchbase Inc. 11 N1QL is Declarative:Top 10 Selling Products SELECT product.name, SUM(items.count) AS unitsSold FROM purchases UNNEST purchases.lineItems AS items JOIN product ON KEYS items.product GROUP BY product ORDER BY unitsSold DESC LIMIT 10 WHAT HOW
  12. 12. ©2015 Couchbase Inc. 12 Sessions on N1QL – Deep Dive  Under the Hood: Couchbase Server 4.0 Architecture May 3 @ 11:30 pm - 12:15 pm, ArchitectureTrack  Deep Dive into N1QL: Power Features and Internals in Couchbase 4.0 May 3 @ 2:30 pm - 3:15 pm, ArchitectureTrack  Tuning Query Performance with N1QL in Couchbase Server 4.0 May 4 @ 1:45 pm – 2:30 pm, ArchitectureTrack  Enterprise Architect’s Perspectives of Couchbase with N1QL May 4 @ 5:15 pm – 6:00 pm, ArchitectureTrack
  13. 13. ©2015 Couchbase Inc. 13 N1QL ConnectsToYour Enterprise Ecosystem Standards-based drivers Integrations, partnerships ODBC / JDBC App CB Node ODBC / JDBC ETL ODBC / JDBC BI ODBC / JDBC Visualization CB Node CB Node
  14. 14. ©2015 Couchbase Inc. 14 Sessions on N1QL – Partners  Operational Analytics with Looker and N1QL- Looker May 3 @ 1:00 pm – 1:45 pm, Big Data Track  Enterprise Data Integration: Using Informatica ETL with Couchbase – Informatica May 3 @ 3:45 pm – 4:30 pm, Big Data Track  Visual Analytics withTableau & Couchbase –Tableau Software May 3 @ 4:30 pm - 5:15 pm, ArchitectureTrack  Open Connectivity: BI, Integration, and Applications on Couchbase using ODBC and JDBC - Simba May 4 @ 1:45 pm – 2:30 pm, Big DataTrack  Metanautix Quest and Couchbase: Scalable Analytics Across NoSQL, RBDMS, Hadoop – Metanautix May 4 @ 3:45 pm – 4:30 pm, Big DataTrack
  15. 15. Indexing
  16. 16. ©2015 Couchbase Inc. 16 Why DoWe Need Indexes? Indexes are used to quickly look up objects meeting user-specified criteria without having to search over every object in the database.
  17. 17. ©2015 Couchbase Inc. 17 What Are the DifferentTypes of Indexes? Primary Indexes Secondary Indexes Spatial Indexes Text Indexes
  18. 18. ©2015 Couchbase Inc. 18 IndexTypes … Let’s Use the Library Analogy Source: http://www.montel.com/en/markets/library/
  19. 19. ©2015 Couchbase Inc. 19 Secondary Indexes Local secondary indexes – Map/Reduce views in 3.0  Co-located with data  Higher write performance  Lower read performance: scatter-gather  Scaling bottleneck with a high number of indexes or data nodes Global secondary indexes (GSI) – New in 4.0  Higher query performance  Async writes to a large number of global indexes  Independently scaled and partitioned  Isolated from Key-Value operations
  20. 20. ©2015 Couchbase Inc. 20 Sessions on Global Secondary Indexes  Introducing Global Secondary Indexes:The New High Performance Indexer with Couchbase 4.0 May 3 @ 1:45 pm - 2:30 pm,ArchitectureTrack  Deep Dive into Global Secondary Indexing Architecture in Couchbase Server 4.0 May 3 @ 3:45 pm - 4:30 pm,ArchitectureTrack
  21. 21. ©2015 Couchbase Inc. 21 Box on Points Box Intersects Multi Dimensions Geo + Others Spatial Indexes  Experimental in 3.0, now GA in 4.0  Performance and stability improvements  GeoJSON output  Bounding-box and range queries on multiple dimensions
  22. 22. ©2015 Couchbase Inc. 22 Session on Spatial Indexes  Introducing SpatialViews for LocationAware Applications with Couchbase Server 4.0 May 4 @ 4:30 pm – 5:15 pm,ArchitectureTrack
  23. 23. ©2015 Couchbase Inc. 23 Text Indexes (Developer Preview) … wise … engineer … … … …, akay1980, … …, akay1980, … engineers engineer Exact Match Inverted Index Apply the same text analysis at search time that we used at index time.
  24. 24. ©2015 Couchbase Inc. 24 Session onText Indexes  A Sneak Peek of CBFT, FullText Search for Couchbase May 3 @ 5:15 pm –6:00 pm,ArchitectureTrack
  25. 25. Multi-Dimensional Scaling
  26. 26. ©2015 Couchbase Inc. 26 Workload and Scaling Horizontal scaling  Partitions a dataset onto one or more homogenous nodes  Each node runs the same mixed workloads  Re-partition dataset with additional hardware capacity Node 8 Index Service Couchbase Cluster Query Service Data Service Node 1
  27. 27. ©2015 Couchbase Inc. 27 Multi-Dimensional Scaling Isolated Service for minimized interference  Independent “zones” for query, index, and data services Minimize indexing and query overhead on core key-value operations. Index Service Couchbase Cluster Query Service Data Service Node 1 Node 8
  28. 28. ©2015 Couchbase Inc. 28 Multi-Dimensional Scaling Independent scalability for the best computational capacity per service Couchbase Cluster node1 Node 8 Node 9 Data Service Index ServiceQuery Service More storage for indexing: scale up index service nodes. More cores for query processing: scale up query service nodes. Node 1
  29. 29. ©2015 Couchbase Inc. 29 Session on Multi-Dimensional Scaling  Multi-Dimensional Scaling:A NewArchitecture for Scaling Big Data Applications May 4 @ 10:30 am – 11:15 am, ArchitectureTrack
  30. 30. ForestDB: Next-Generation Storage Engine
  31. 31. ©2015 Couchbase Inc. 31 Common Storage Structures – B+-Tree 31 Reads Writes Engines B+-Tree Good read performance if the fan-out is high (“short” tree) for small fixed-length keys. Read performance degrades for variable-length keys. Update-In-Place results in random writes and bad write latency. Append-Only file improves write performance but requires periodic compaction. BerkeleyDB, InnoDB, Couchstore (append-only), WiredTiger B+ 04/26 … … … Key Value (or Pointer) longer keys
  32. 32. ©2015 Couchbase Inc. 32 Common Storage Structures – LSM-Tree 32 Reads Writes Engines LSM- Tree Reads may have to traverse multiple trees – typically worse than B+ tree. WAL(Write-Ahead Log) improves writes with in-memory trees that are appended to the end of the log. LevelDB, RocksDB, Cassandra, WiredTiger LSM … In-memory Sequential log flush/merge merge C1 tree C2 tree merge Capacity increases exponentially
  33. 33. ©2015 Couchbase Inc. 33 Fast Storage – ForestDB Fundamentally rethinking the requirements for fast storage  Compact and efficient storage for a variety of data  Unified engine that performs well for various workloads  Unified engine that scales from small devices to large servers  Optimized for new SSD storage technology 33 ForestDB provides a compact index structure that significantly reduces the disk I/O and write amplification.
  34. 34. ©2015 Couchbase Inc. 34 ForestDB ForestDB Evaluations: LevelDB, RocksDB 34 Throughput UP TO FASTER 6X Future Proof FITTED FOR SSD Efficiency UP TO 5XCOMPACT
  35. 35. ©2015 Couchbase Inc. 35 Trie (prefix tree) for which the nodes are B+-Trees  HB+-Trie was originally presented at ACM SIGMOD 2011 Programming Contest, by Jung-Sang Ahn who works at Couchbase (http://db.csail.mit.edu/sigmod11contest/sigmod_2011_contest_poster_jungsang_ahn.pdf) HB+-Trie (Hierarchical B+-Trie)
  36. 36. ©2015 Couchbase Inc. 36 Sessions on ForestDB  Next Generation Storage Engine: ForestDB May 3 @ 4:30 pm – 5:15 pm,ArchitectureTrack  Under the hood ForestDB: Performance on SSDs and File Systems May 4 @ 2:30 pm – 3:15 pm,ArchitectureTrack  Intel: Next Generation SSDs and ForestDB: Next Generation Storage Engine May 4 @ 2:30 pm – 3:15 pm,ArchitectureTrack
  37. 37. Security
  38. 38. ©2015 Couchbase Inc. 38 Previously… In 2.2 In 2.5 In 3.0 New in 4.0 SASL AuthN with Bucket Passwords Admin User Secure Build Platform Read-Only User Easy Admin Password Reset Non-Root User Deployments Secure Communication for XDCR Encrypted Client- Server Communication Encrypted Admin Access Access Log Data-at-Rest Encryption • Simplified compliance with admin auditing • External identity management for admins using LDAP Couchbase Security Features In a few slides .. 38
  39. 39. ©2015 Couchbase Inc. 39 External Identity Management Using LDAP 39 Centralized identity management  Define multiple read-only admins and full-admins  Centralized security policy management for admin accounts for stronger passwords, password rotation, and auto lockouts Individual accountability; simplified compliance  Define UIDs in LDAP, and map UIDs to the read-only/full admin role in Couchbase  Comprehensive audit trails with LDAP UIDs in audit records
  40. 40. ©2015 Couchbase Inc. 40 Admin Auditing in Couchbase 40 Rich audit events  Over 25+ different, detailed admin audit events  Auditing for tools including backup Configurable auditing  Configurable file target  Support for time-based log rotation and audit filtering Easy integration  JSON format allows for easy integration with downstream systems using flume, logstash, and syslogd
  41. 41. ©2015 Couchbase Inc. 41 Auditing a successful login 41 { "timestamp":"2015-02-20T08:48:49.408-08:00", "id":8192, "name":"login success", "description":"Successful login to couchbase cluster", "role":"admin", "real_userid": { "source":"ns_server", "user":"bjones” }, "sessionid":"0fd0b5305d1561ca2b10f9d795819b2e", "remote":{"ip":"172.23.107.165", "port":59383} } WHEN WH O WHAT HO W
  42. 42. ©2015 Couchbase Inc. 42 Sessions on Security  Security Features in Couchbase Server May 3 @ 3:45 pm – 4:30 pm, OperationsTrack  SecuringYour Couchbase Server Deployment UsingVormetric May 4 @ 10:30 pm –11:15 pm, OperationsTrack
  43. 43. Querying with N1QL Indexing Multi-Dimensional Scaling ForestDB: Next-Generation Storage Engine Security
  44. 44. Get Started withCouchbase Server 4.0: www.couchbase.com/beta GetTrained on Couchbase: training.couchbase.com

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