Safe Harbor Statement
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2 Safe Harbor Statement The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle s products remains at the sole discretion of Oracle. 2
3 Data Management in the Hybrid Cloud Jan Tjernberg Master Principal Sales Consultant, Core Technology Oracle Svenska
4 Data management alternatives Data stores available from Oracle: And many more from other vendors... On-premise & in the Cloud => Hybrid Cloud Hadoop Cloudera dist.... Integration becomes even more important and creates challenges: # of moving parts => Cost & Complexity Many copies of data Performance Data protection and consistency Security Supportability... Why so many different data stores? 4
5 NoSQL or Relational?? NoSQL DBMS Schema private to application Collections of data objects Basic Availability, Soft-state, Eventual consistency Relational DBMS Schema shared by multiple applications Inter-related collections of data objects Atomic, Consistent, Isolated, Durable 5
6 Storage Choices Hadoop, NoSQL, Relational HDFS Oracle NoSQL DB Oracle Database File System Database Database Parallel scanning Indexed storage Indexed, Cached, In-Memory Batch Oriented No inherent structure Real-Time, web-scale specialized applications Simple data structure General purpose SQL platform, multiple applications, ODBC, JDBC Complex data structures, rich SQL processing 6
7 Storage Choices Hadoop, NoSQL, Relational HDFS Oracle NoSQL DB Oracle Database File System Database Database Parallel scanning Indexed storage Indexed, Cached, In-Memory Batch Oriented No inherent structure Real-Time, web-scale specialized applications Simple data structure General purpose SQL platform, multiple applications, ODBC, JDBC Complex data structures, rich SQL processing Horizontal Scalability Horizontal Scalability Vertical & Horizontal Scalability High volume writes Limited functionality, roll-your-own applications High volume random reads and writes Simple get/put high speed storage, flex configuration High volume OLTP with 2-PC Security, Backup/Restore, Data life cycle mgmt, XML, etc. 7
8 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
9 Gartner s view on Data Stores October 2016 Strategic Planning Assumptions By 2017, all leading operational DBMSs will offer multiple data models, relational and nonrelational, in a single DBMS platform. Through 2018, 50% of operational DBMS vendors with less than $50 million in annual revenue will disappear due to acquisitions, mergers or business failures. Ref: 9
10 Announcing Oracle Database 12c Release 2 on Oracle Cloud Available now Exadata Express Cloud Service Enterprise Cloud Service Available November Exadata Cloud Service Available December Exadata Cloud Machine Copyright 2016, Oracle and/or its affiliates. All rights reserved. 10
11 Oracle Database Cloud Service Full Instance Editions Enterprise Edition (EE) adds Transparent Data Encryption (TDE) All standard EE features Standard Edition Full database instance Up to 16 OCPUs Exadata Express One PDB on Exadata One OCPU, 20 GB/50 GB EE High Performance adds Multitenant Data Guard Partitioning Advanced Compression Advanced Security, Label Security, Database Vault Real Application Testing OLAP, Analytics, Spatial and Graph Management Packs EE Extreme Performance adds Real Application Clusters (RAC)* In Memory Active Data Guard Copyright 2014 Oracle and/or its affiliates. All rights reserved.
12 Breakthrough: Dual Format In-Memory Database Memory SALES Row Format Memory SALES Column Format BOTH row and column inmemory formats for same table Simultaneously active and transactionally consistent Analytics & reporting use new in-memory Column format OLTP uses proven row format 12
13 Rows Inserted per second The Slow down on OLTP From Analytic Indexes Insert rate decreases as number of indexes increases # of Fully Cached Indexes (Disk Indexes are much slower) 13 13
14 The Power of Oracle SQL for a wide variety of Big Data types Structured data Numeric, string, date, Row and column formats Unstructured data LOBs Text XML JSON Spatial Graph Multimedia 14
15 Fast SQL access for Relational, Hadoop and NoSQL Using Oracle Big Data SQL Unified SQL language for all data sources With full power of Oracle SQL Massively parallel, distributed query processing Local processing using Smart Scan technology Scalable joins between data sources Secure data access Redaction and row-based security on all data sources Big Data SQL 15
16 Users Oracle s Advanced Analytics (Machine Learning Platform) Multiple interfaces across platforms SQL, R, GUI, Dashboards, Apps Information Producers Information Consumers R programmers Data & Business Analysts Business Analysts/Mgrs Domain End Users R Client SQL Developer/ Oracle Data Miner OBIEE Applications Platform Hadoop Oracle Database Enterprise Edition HQL ORAAH Parallel, distributed algorithms Oracle Advanced Analytics - Database Option SQL Data Mining, ML & Analytic Functions + R Integration for Scalable, Distributed, Parallel in-db ML Execution Oracle Database 12c Oracle Cloud
17 Engineered for Clouds and Big Data Database as a Service Cloud Big Data 17
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