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Preview of Oracle Database 12c In-Memory Option 1 Copyright © 2013, Oracle and/or its affiliates. All rights reserved. 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 Copyright © 2013, Oracle and/or its affiliates. All rights reserved. 2 Oracle Database In-Memory Option Goals 100X Faster Queries: Real-Time Analytics Get instantaneous query results Querying OLTP database or data warehouse 2X Faster Transaction Processing Trivial to Deploy for All Applications and Customers 3 Copyright © 2013, Oracle and/or its affiliates. All rights reserved. Confidential – Oracle Internal 3 Optimizing Transaction and Query Performance Row Format Databases versus Column Format Databases SALES Transactions run faster on row format ORDER Row – Fast for processing few rows, many columns – Example: Insert or query a sales order SALES Column S T A T E Analytics run faster on column format – Fast for processing few columns, many rows – Example: Report on sales totals by state Until Now You Choose One Format and Suffer Tradeoffs 4 Copyright © 2013, Oracle and/or its affiliates. All rights reserved. Confidential – Oracle Internal 4 Breakthrough: Dual Format In-Memory Database Memory Memory Sales Row Format Sales Column Format BOTH row and column in-memory formats for same table OLTP Simultaneously active and Analytics transactionally consistent Analytics & reporting use New Column format OLTP uses row format 5 Copyright © 2013, Oracle and/or its affiliates. All rights reserved. Confidential – Oracle Internal 5 Oracle In-Memory Columnar Technology Pure in-memory format with no logging Memory Near zero overhead on changes Even for OLTP Uses memory-optimized compression 2x to 10x memory reduction Pure Columnar Data loaded in-memory for active tables or partitions - on startup or first access For in-memory tables, >90% of memory will be used for column format Row format needs little memory 6 Copyright © 2013, Oracle and/or its affiliates. All rights reserved. Confidential – Oracle Internal 6 Find Any Business Data in Sub-second Example: Find all sales in state of CA • Each CPU scans local in-memory columns In-Memory Column Store Sales State column >100X Faster Scans use super fast SIMD vector instructions “CA” scan rate per CPU core CPU 7 Copyright © 2013, Oracle and/or its affiliates. All rights reserved. Confidential – Oracle Internal Load multiple State values SIMD Compare Compare all all values values in 1 in 1 cycle instruction Vector Register Billions of rows/sec 7 Scans and Combines Data from Multiple Tables Example: Find all sales in outlet stores Stores Converts join processing into fast column scans Joins up to 10x faster T Y P E Sales Storeid in 15,38,64 Type=outlet 8 Copyright © 2013, Oracle and/or its affiliates. All rights reserved. Confidential – Oracle Internal S T O R E I D A M O U N T Sum 8 Generate Reports In Sub-second Example: Show sales trends for footwear products in outlet stores Dynamically creates in-memory report outline Stores Sales Report contents populated In-Memory Report Outline during fact scan Reports up to 20x faster without predefined cubes 9 Copyright © 2013, Oracle and/or its affiliates. All rights reserved. Confidential – Oracle Internal Products Sales 9 OLTP is Slowed Down by Analytic Indexes Most Indexes in mixed-use OLTP (e.g. ERP) databases are only used for analytics Table 1 to 3 OLTP Indexes 5 to 15 Analytics Indexes Indexes work well for known access patterns both in-memory and on-disk But every change to the table requires changing all analytic indexes – Slow! 10 Copyright © 2013, Oracle and/or its affiliates. All rights reserved. Confidential – Oracle Internal 10 Column Store Replaces Analytic Indexes In-Memory Column Store replaces analytic indexes for tables that fit in memory Table 1 to 3 OLTP Indexes In-Memory Column Store Removes analytic index overhead on changes Both predefined and ad-hoc analytic queries run fast Less tuning & admin needed OLTP & batch often run 2x or more faster 11 Copyright © 2013, Oracle and/or its affiliates. All rights reserved. Confidential – Oracle Internal 11 Demonstration at Oracle Openworld 2013 Performance of columnar scan vs. row scan - Both in memory 12 Copyright © 2013, Oracle and/or its affiliates. All rights reserved. Confidential – Oracle Internal 12 Extreme Capacity and Cost Effectiveness Size not limited by memory DRAM Hottest Data PCI FLASH Active Data Data transparently accessible across tiers Each tier has specialized algorithms & compression Capacity of Disk IOs of Flash Speed of DRAM 13 Copyright © 2013, Oracle and/or its affiliates. All rights reserved. Confidential – Oracle Internal DISK Cold Data 13 Scale-Out In-Memory Database to Any Size Scale-Out across servers to In Memory Column Store In Memory Column Store grow memory and CPUs In-Memory queries are parallelized across servers to access local column data In Memory Column Store In Memory Column Store Direct-to-wire InfiniBand protocol speeds messaging 14 Copyright © 2013, Oracle and/or its affiliates. All rights reserved. Confidential – Oracle Internal 14 Scale-Up for Maximum In-Memory Performance Scale-Up on large SMPs SMP scaling removes overhead of distributing queries across servers or coordinating transactions Inter-processor bandwidth far exceeds any network 15 Copyright © 2013, Oracle and/or its affiliates. All rights reserved. Confidential – Oracle Internal 15 Oracle In-Memory is Trivial to Deploy 1. Configure Memory Capacity inmemory_area = XXXX GB 2. Configure tables or partitions to be in memory alter table | partition … inmemory; 3. Later Drop analytic indexes to speed up OLTP 16 Copyright © 2013, Oracle and/or its affiliates. All rights reserved. Confidential – Oracle Internal 16 Oracle In-Memory is Transparent to Applications Existing Applications Just Run Faster Full Functionality Trivial to Implement Fully Compatible DB as a Service Ready - No restrictions on SQL - No migration of data or change of product - All existing applications run unchanged - Oracle Multitenant in-memory And All Other Apps that Support Oracle Database Uniquely Achieves All In-Memory Benefits With No Application Changes 17 Copyright © 2013, Oracle and/or its affiliates. All rights reserved. Confidential – Oracle Internal 17 Oracle In-Memory Delivers Extreme Availability Data Guard & GoldenGate Pure In-Memory format does not change Oracle’s storage format, logging, backup, recovery, etc. All Oracle’s mature availability RAC technologies work transparently Protection from all failures ASM Node, site, corruption, human error, change, etc. 18 Copyright © 2013, Oracle and/or its affiliates. All rights reserved. Confidential – Oracle Internal RMAN 18 Summary: Oracle Database In-Memory Option • 100X Faster Queries: Real-Time Analytics Querying OLTP database or data warehouse • 2X Increase Transaction Processing Rates • Less Management and Tuning • Best of Memory, Flash, Disk • Scale-Out and Scale-Up • Extreme Availability Trivial to Deploy for All Applications and Customers 19 Copyright © 2013, Oracle and/or its affiliates. All rights reserved. Confidential – Oracle Internal 19 APPENDIX Relation of Database In-Memory Option to TimesTen and Exadata 20 Copyright © 2013, Oracle and/or its affiliates. All rights reserved. Confidential – Oracle Internal Oracle Database In-Memory Products TimesTen In-Memory Database Oracle Database In-Memory Embedded in custom applications Extreme low latency OLTP workloads (Microsecond Response Time) Adaptive In-Memory Cache for Exalytics In-Memory Machine Scalable In-Memory Database for any type of application workload Combines best of DRAM, flash, disk Application Application 21 Copyright © 2013, Oracle and/or its affiliates. All rights reserved. Application Confidential – Oracle Internal 21 TimesTen In-Memory Database and Columnar TimesTen Grid TimesTen is adding scale-out capabilities – For both OLTP and analytics TimesTen is adding columnar technologies to accelerate Analytics Scale-Out In-Memory DB – Core columnar processing engine is shared between Oracle and Timesten – Embedded Analytics engine Columnar 22 Copyright © 2013, Oracle and/or its affiliates. All rights reserved. Confidential – Oracle Internal 22 Oracle Database In-Memory Option on Exadata • Exadata extends fast analytics from in-memory to flash and disk for highest capacity and lowest cost • Scale-out intelligent flash optimized storage: >100GB/sec from flash • Exadata DB as a Service In-Memory delivers consolidation, ultra fast performance, best agility, and lowest cost • Highest performance applications run in-memory • Applications that perform well today use cost-effective disk and flash • Expect special optimizations for Database In-Memory on Exadata • E.g. Fastest communication with InfiniBand Direct to Wire protocol • Exadata is a standardized, pre-configured, pre-tuned, pre-tested platform for database in memory, on flash, and on disk 23 Copyright © 2013, Oracle and/or its affiliates. All rights reserved. Confidential – Oracle Internal 23 Platform of the Future Platform Engineered for Database Database Engineered for Cloud and Consolidation Enterprise DBaaS Optimized for latest technologies In-Memory Database PCI Flash for fastest IO Disk for highest capacity Optimal compression at every tier Fastest Communication For all workloads – running together Highest performance, lowest cost, most available, most scalable 24 Copyright © 2013, Oracle and/or its affiliates. All rights reserved. Confidential – Oracle Internal 24 25 Copyright © 2013, Oracle and/or its affiliates. All rights reserved. Confidential – Oracle Internal 26 Copyright © 2013, Oracle and/or its affiliates. All rights reserved. Confidential – Oracle Internal