Oracle Database 12c Release 1 (12.1.0.2 )

1. Oracle Database 12c Release 1 (12.1.0.2) Thomas Kyte http://asktom.oracle.com/ Oracle Server Technologies

2. Oracle Database 12c Release 1 (12.1.0.2) 1 Oracle Database 12c Overview Oracle Database In-Memory Oracle Database 12c for the Developer Oracle Database 12c for Big Data Oracle Multitenant Other Improvements 2 3 4 5 6

3. Oracle Database 12c (12.1.0.1) Oracle Multitenant Database consolidation Fast Provisioning Manage many as one Oracle Automatic Data Optimization Smart Compression Automate Tiering Data Guard Far Sync Zero data loss over large distances

4. Oracle Database 12c (12.1.0.1) Application Continuity Replay of failed transaction Data Redaction Masks application data dynamically Transparent to application Pattern Matching Sophisticated inter row pattern analysis

5. Oracle Database 12c Release 1 (12.1.0.2) Exploit memory to improve performance Simplify access to Big Data Improve application developers experience Continue to improve consolidation

6. Oracle Database 12c Release 1 (12.1.0.2) 1 Oracle Database 12c Overview Oracle Database In-Memory Oracle Database 12c for the Developer Oracle Database 12c for Big Data Oracle Multitenant Other Improvements 2 3 4 5 6

7. Flip Flops Core 1993 ~$25/mb; $26,214,400/tb 2014 ~$0.007/mb; $7,645/tb ICs on board SIMMs DIMMS Big Drives Floppy Small Drives Flash SSD

8. Oracle Database In-Memory Goals Exploit latest generation hardware Accelerate OLTP No Changes to Applications Real Time Analytics CPU

9. Row Format Databases vs. Column Format Databases Row SALES • Transactions run faster on row format • Example: Insert or query a sales order • Fast processing few rows, many columns Column • Analytics run faster on column format • Example : Report on sales totals by region • Fast accessing few columns, many rows SALES Until Now Must Choose One Format and Suffer Tradeoffs

10. Oracle In-Memory Columnar Technology Pure in-memory column format Not persistent, and no logging Quick to change data: fast OLTP 2x to 20x compression Enabled at table or partition level Available on all hardware platforms Pure In-Memory Columnar SALES

11. Scans Billions of Rows per Second per CPU Core Memory Each CPU core scans local in-memory columns Scans use fast SIMD vector instructions Originally designed for graphics & science Billions of rows/sec scan rate per CPU core Example: Find all sales in region of CA REGION CPU CA Load multiple region values Vector Compare all values an 1 cycle CA CA Vector Register CA > 100x Faster

12. Oracle Database 12c Release 1 (12.1.0.2) 1 Oracle Database 12c Overview Oracle Database In-Memory Oracle Database 12c for the Developer Oracle Database 12c for Big Data Oracle Multitenant Other Improvements 2 3 4 5 6

13. Oracle Database 12c Release 1 (12.1.0.2) Flexible Schema development Oracle Database 12c JSON JSON SQL Via RESTful service Via Native APIs Data analyzed via SQL Data persisted in database In JSON

14. Querying JSON Sample JSON in column customers.document select c.document.firstName, c.document.lastName, c.document.address.city, c.document.phoneNumbers from customers c; Simplified syntax for simple queries { "firstName": "John", “lastName”: "Smith", "age": 25, "address": { "streetAddress": "21 2nd Street", "city": "New York", "state": "NY", "postalCode": "10021“, "isBusiness" : false}, "phoneNumbers": [ { "type": "home", "number": "212 555-1234“ }, { "type": "fax", "number": "646 555-4567“ } ] }

15. Oracle REST Data Services Enabling RESTful access to Oracle Database • Provides data access consistent with modern App Dev frameworks • Can map standard http(s) URI RESTful gets and posts to SQL • Can declaratively returns results in JSON format • JavaScript framework friendly • Can support high numbers of end users • Services • HTTP(s) relational data access • Oracle JSON collection based schemaless access • Oracle NoSQL access over HTTP • Oracle APEX mid-tier, web toolkit applications, mod_plsql replacement • Formally known as Oracle APEX Listener • Supported feature of the Oracle Database since 2010 • Ships with Oracle Database 12cRelease 1 (12.1.0.2)

16. Oracle REST Data Services Schemaless development using JSON Collection API (12.1.0.2) Oracle REST Data Services Auto Generated SQL JSON Collection API URI Pass Back JSON Transform JSON Oracle Database HTTP(S) client • Data stored in Oracle Database as JSON documents • App Developer make standard HTTP(S) calls to JSON Collection APIs

17. Oracle REST Data Services Serving JSON results from relational data Oracle REST Data Services URI Map and Bind SQL Transform to JSON JSON Transform SQL Result Set HTTP(S) client Oracle Database • Data stored in standard relational tables and columns • Oracle REST Data Services (ORDS) Developer defines URI<>SQL mapping • App Developer calls named URI over HTTP(S) gets and posts

18. Oracle REST Data Services Serving JSON results with Oracle NoSQL Database (ORDS 3.1) Oracle REST Data Services URI Key-Value Lookup NoSQL API Pass Back JSON Transform JSON HTTP(S) client Oracle NoSQL Database • Oracle REST Data Services provides HTTP(s) access to Oracle NoSQL • Oracle NoSQL is embedded within ORDS and can also access remote DB

19. Oracle Database 12c Release 1 (12.1.0.2) 1 Oracle Database 12c Overview Oracle Database In-Memory Oracle Database 12c for the Developer Oracle Database 12c for Big Data Oracle Multitenant Other Improvements 2 3 4 5 6

20. SQL is Critical “….the complexity of dealing with a non-ACID data store in every part of our business logic would be too great, and there was simply no way our business could function without SQL queries.” Google, VLDB 2013 “[Facebook] started in the Hadoop world. We are now bringing in relational to enhance that. ... [we] realized that using the wrong technology for certain kinds of problems can be difficult.” Ken Rudin, Facebook, TDWI 2013 http://tdwi.org/articles/2013/05/06/facebooks-relational-platform.aspx https://www.linkedin.com/groups/Find-out-why-Google-decided-4434815.S.273792742

21. Oracle Support for Any Data Management System Relational Hadoop NoSQL • Change the Business • Scale-out, low cost store • Collect any data • Map-reduce, SQL • Analytic applications • Scale the Business • Scale-out, low cost store • Collect key-value data • Find data by key • Web applications • Run the Business • Scale-out and scale-up • Collect any data • SQL • Transactional and analytic applications for the enterprise • Secure and highly available

22. Overcoming Barriers to Adoption of New Technologies INTEGRATION SKILLS SECURITY SQL Database Security on All Data EngineeredSystems SQL onAll Data Confidential

23. Oracle Big Data SQL One fast SQL query , onallyour data. • Oracle SQL on Hadoop and beyond • With a Smart Scan service as in Exadata • With native SQL operators • With the security and certainty of Oracle Database Oracle Confidential – Internal/Restricted/Highly Restricted

24. Accessing Big Data Select w.sess_id, w.cust_id, w.page_id From web_logs w Where w.source_country = ‘Brazil’ And w.category = ‘TV’ And w.channel = ‘Mobile’ Without SQL Push Down Request for Data 100’s of Terabytes of Data WEB_LOGS Hadoop Cluster All columns and rows from the table are returned Low utilization of available resources High load on database server

25. Big Data SQL Push Down Select w.sess_id, w.cust_id, w.page_id From web_logs w Where w.source_country = ‘Brazil’ And w.category = ‘TV’ And w.channel = ‘Mobile’ WithSQL Push Down Big Data SQL Server SQL shipped to BDA 10’s of Gigabytes of Data WEB_LOGS Hadoop Cluster Only columns and rows needed to answer query are returned Good utilization of available resources. SQL executed on Hadoop cluster Lower load on Server, Faster response

26. Big Data SQL Push Down Select w.sess_id, w.cust_id, w.page_id, c.name From web_logs w, customers c Where w.source_country = ‘Brazil’ And w.category = ‘TV’ And w.channel = ‘Mobile’ And c.customer_id = w.cust_id WithSQL Push Down Big Data SQL Server SQL shipped to BDA 10’s of Gigabytes of Data WEB_LOGS CUSTOMERS Hadoop Cluster Only columns and rows needed to answer query are returned Good utilization of available resources. SQL executed on Hadoop cluster Data joined between CUSTOMERS and WEB_LOGS on server

27. Big Data SQL Push Down Select w.sess_id, w.cust_id, w.page_id, c.name From web_logs w, customers c Where w.source_country = ‘Brazil’ And w.category = ‘TV’ And w.channel = ‘Mobile’ And c.customer_id = w.cust_id WithSQL Push Down Big Data SQL Server • SQL Push Downs supported by Big Data SQL • Hadoopscans (InputFormat, SerDe) • JSON parsing • WHERE clause evaluation • Column projection • Bloom filters for faster join SQL shipped to BDA 10’s of Gigabytes of Data WEB_LOGS CUSTOMERS Hadoop Cluster Only columns and rows needed to answer query are returned Good utilization of available resources. SQL executed on Hadoop cluster Data joined between CUSTOMERS and WEB_LOGS on server

28. New Data Sources for Oracle External Tables • New set of properties • ORACLE_HIVE and ORACLE_HDFS access drivers • Identify a Hadoop cluster, data source, column mapping, error handling, overflow handling, logging • New table metadata passed from Oracle DDL to Hadoopreaders at query execution • Architected for extensibility • StorageHandler capability enables future support for other data sources • Examples:MongoDB, HBase, Oracle NoSQL DB • CREATE TABLE web_logs • (click VARCHAR2(4000)) • ORGANIZATION EXTERNAL •  ( TYPE ORACLE_HIVE • DEFAULT DIRECTORY Dir1 • ACCESS PARAMETERS • ( • com.oracle.bigdata.tablename logs • com.oracle.bigdata.clustermycluster) • ) • REJECT LIMIT UNLIMITED

29. Oracle Database 12c Release 1 (12.1.0.2) 1 Oracle Database 12c Overview Oracle Database In-Memory Oracle Database 12c for the Developer Oracle Database 12c for Big Data Oracle Multitenant Other Improvements 2 3 4 5 6

30. Oracle Multitenant New architecture for consolidating databases and simplifying operations • Self-contained PDB for each application • Applications run unchanged • Rapid provisioning (via clones) • Portability (via pluggability) DW ERP CRM • Common operations performed at CDB level • Manage many as one (upgrade, HA, backup) • Granular control when appropriate • Shared memory and background processes • More applications per server

31. Multitenant New Features in 12.1.0.2 Subset by tablespace Metadata-only clone Remote clone (including snapshots) File system-agnostic cloning via dNFS (clonedb = true) New SQL clause to aggregate data across PDBs select ENAME from containers(scott.EMP)where CON_ID in (45, 49); New “standbys” clause • (all | none) Nologging clause at PDB level Flashback data archive, transaction query & backout Temporal SQL Support Compatible with DB In-Memory Maintains state of PDBs between CDB restarts SQL Cloning Cross PDB Queries PRIMARY STANDBY Standby & Logging Additional Features

32. Oracle Database 12c Release 1 (12.1.0.2) 1 Oracle Database 12c Overview Oracle Database In-Memory Oracle Database 12c for the Developer Oracle Database 12c for Big Data Oracle Multitenant Other Improvements 2 3 4 5 6

33. Performance Improvements

34. Advanced Index Compression Compresses indexes to reduce their overall storage requirement Less space required on disk Better use of the database cache Indexes are compressed by between 1 – 3 times Little or no discernable overhead Compression Advisor extended to describe the possible benefits of this feature

35. Attribute Clustering Ordering of data so that rows are stored near one another based on column values Improved query performance and concurrency Reduced physical data access trough smart IO Significant IO reduction for highly selective operations Optimized space utilization Less need for indexes Improved compression ratios through data clustering Full application transparency Any application will benefit Benefits :

36. Zone Maps Persisted storage index Stores minimum and maximum of specified columns Analogous to a coarse index structure Much more compact than an index Zone maps filter out what you don’t need, indexes find what you do need Significant performance benefits with complete application transparency IO reduction for table scans with predicates on the table itself or even a joined table using join zone maps (a.k.a. “hierarchical zone map”) Benefits are most significant with ordered data Used in combination with attribute clustering or data that is naturally ordered

37. Approximate Count Distinct Not every query requires a completely accurate result “How many distinct individuals visited our website last week?” New SQL function for approximate results for COUNT DISTINCT aggregates APPROX_COUNT_DISTINCT() Approximate results can be significantly faster and use less resources than exact calculations 5x to 50x ++ times faster (depending upon number of distinct values and complexity of SQL) Accuracy > 97% (with 95% confidence)

38. Rapid Home Provisioning

39. Oracle Rapid Home Provisioning Install Once Use Many Patching is complex and time consuming Even when automated New way to deploy upgrades Create reference homes on Centralized Home Server Apply patches once (Enterprise) on Home Server Distribute homes on-demand or policy Fast and Efficient Rapid distribution (network efficient) Space efficient (snapshots) Local caches

40. Oracle Rapid Home Provisioning Oracle Enterprise Manager Database Cloud Provisioning Monitoring and Configuration Capacity and Resource Patching Performance and Tuning Service Level Application Database Grid Cluster Cluster Cluster NFS Mount Cluster Cluster Cluster Grid Home Server Service Catalog Local Gold Image Differential Copy S/W Distribution

41. Database Backup Logging Recovery Appliance

42. Database Backup Logging Recovery ApplianceA New Approach to Data protection in the Enterprise Backup Windows Eliminated. No more Full Backups Sub second transaction protection of critical data Improved System Availability by offloading backup processing End to end data protection by block validation throughout its lifecycle

43. Architected for Protection of Critical Data CLOUD SCALE DELTA PUSH DELTA STORE CLOUD SCALE • Scales to 1000s of Clients • Petabytes of Data • No expensive backup agents • DBs access and send only changed data • Minimal impact on production servers • Real-time redo ship for near-zero data loss • Validated, compressed database change data • Fast restores to any point-in-time using deltas • Built on Exadata scaling & resilience • Copy to tape: no production server load • Tapes utilized all day • Restore directly from tape

44. Oracle Key Vault

45. Key Management Challenges Heard from Customers Servers Databases Middleware • Management Challenges • Proliferation of encryption wallets and keys • Authorized sharing of keys • Key availability, retention, and recovery • Custody of keys and key storage files • Regulatory Challenges • Physical separation of keys from encrypted data • Periodic key rotations • Monitoring and auditing of keys • Long-term retention of keys and encrypted data

46. Key Management with Oracle Key Vault KEY VAULT • Centralized management of keys, secrets, Oracle Wallets, Java Keystores and more • Optimized solution for Oracle Stack (Database, Middleware, Systems) • Supports industry standard OASIS KMIP protocol

47. Oracle Key Vault High-Level Architecture KEY VAULT Standby Middleware Administration Console, Alerts, Reports Databases Secure Backups Servers = Oracle Wallet = Certificate = Credential File = Java Keystore = Server Password

48. Oracle Advanced Security Transparent Data Encryption (TDE) KEY VAULT Oracle Wallet Scenarios Data Guard Multiple DBs Same Machine RAC Single Instance GoldenGate

49. Oracle Advanced Security Transparent Data Encryption (TDE) KEY VAULT Direct Connection Scenarios Data Guard RAC Single Instance Multiple DBs Same Machine GoldenGate

50. Oracle Key Vault Software Appliance Platform • Turnkey solution based on hardened stack • Includes Oracle Database and security options • Open x86-64 hardware to choose from • Easy to install, configure, deploy, and patch • Separation of duties for administrative users • Full auditing, preconfigured reports, and alerts