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Larry Ellison Introduces Oracle Database In-Memory

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On June 10, Larry Ellison launched Oracle Database In-Memory: Delivering on the Promise of the Real-Time Enterprise. Larry Ellison described how the ability to combine real-time data analysis with sub-second transactions on existing applications enables organizations to become Real-Time Enterprises that quickly make data-driven decisions, respond instantly to customer’s demands, and continuously optimize key processes. Watch the launch webcast replay here: http://www.oracle.com/us/corporate/events/dbim/index.html

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Larry Ellison Introduces Oracle Database In-Memory

  1. 1. Larry Ellison Chief Executive Officer, Oracle Oracle Confidential – Internal/Restricted/Highly RestrictedCopyright © 2014 Oracle and/or its affiliates. All rights reserved. | Oracle Database In-Memory Powering the Real-Time Enterprise
  2. 2. 2 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Oracle Database In-Memory Option Powering the Real-Time Enterprise Available in July
  3. 3. 3 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Oracle Database In-Memory Option: Goals  100X Faster Queries: Real-Time Analytics • Instantaneous Queries on OLTP Database or Data Warehouse  2x Faster OLTP • Insert rows 3x to 4x faster  Transparent: No application changes • Minutes to Implement
  4. 4. 4 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Oracle 12c Stores Data in Both Formats Simultaneously Optimizing Transaction and Query Performance Row Format Databases versus Column Format Databases Row  Transactions run faster on row format – Example: insert or query a sales order – Fast processing of few rows, many columns Column  Analytics run faster on column format – Example: report on sales totals by region – Fast accessing of few columns, many rows ORDER SALES SALESREGION
  5. 5. 5 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.  BOTH row and column formats for same data/table  Simultaneously active and transactionally consistent  100X Faster Analytics in-memory column format  2X faster OLTP: row format Innovation: Dual Format In-Memory Database Column Format Memory Row Format Memory AnalyticsOLTP Sales Sales Sales
  6. 6. 6 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Oracle In-Memory Column Format Pure In-Memory Pure Columnar  2X to 20X compression: Faster Scans  No data change logging: Faster OLTP  Enabled at table or partition level  Available on all hardware platforms Sales Sales
  7. 7. 7 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Scans Billions of Rows per Second per CPU Core SIMD Compare all values in 1 cycle Vector Compare all values in 1 cycle Load multiple Region values Vector Register In-Memory Column Store Sales Example: Find all sales in region of CA “CA” >100X Faster • Each CPU core scans local in-memory columns  Scans use super fast SIMD vector instructions  Billions of rows/sec scan rate per CPU core CPU R E G I O N
  8. 8. 8 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. 10x Faster Joining and Combining Data SalesStores Type=outlet Example: Find total sales in outlet stores Storeid in 15,38,64 S T O R E I D A M O U N T  Converts join processing into fast column scans  Joins tables 10x faster Sum S T O R E I D T Y P E
  9. 9. 9 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Generate Reports Instantly In-Memory Report Outline Example: Report sales of footwear in outlet stores Products Stores Sales Footwear Sales  Dynamically creates in-memory report outline  Then report outline filled-in during fast fact scan  Reports 20x faster without predefined cubes Outlets Footwear
  10. 10. 10 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. OLTP is Slowed by Analytic Indexes Table 1 to 3 OLTP Indexes 10 to 20 Analytics Indexes  Most OLTP Indexes (e.g. ERP) are only used for analytic queries  Inserting one row into a table requires updating 10-20 analytic indexes: Slow!  Indexes only speed up anticipated queries & reports
  11. 11. 11 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Column Store Replaces Analytic Indexes Table 1 to 3 OLTP Indexes  100x Faster analytics  Works on any columns  Better for ad-hoc analytics  Less tuning required • 2x Faster OLTP and Batch • Column store not logged • Row Insert cost is lower In-Memory Column Store
  12. 12. 12 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Scale-Out In-Memory Database to Any Size In Memory Column Store  Scale-Out across servers to grow memory and CPUs  In-Memory queries parallelized across servers to access local column data  Direct-to-wire InfiniBand protocol speeds messaging In Memory Column Store In Memory Column Store In Memory Column Store
  13. 13. 13 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. In-Memory Speed + Capacity of Low Cost Disk  Size not limited by memory  Data transparently moves between tiers  Each tier has specialized algorithms & compression Speed of DRAM I/Os of Flash Cost of Disk DISK PCI FLASH DRAM Cold Data Hottest Data Active Data
  14. 14. 14 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Scale-Up for Maximum In-Memory Performance  Scale-Up on large SMPs  SMP scaling removes overhead of distributing queries across servers  Memory interconnect far faster than any network M6-32 Big Memory Machine 32 TB DRAM 32 Socket, 384 Cores 3 Terabyte/sec Bandwidth
  15. 15. 15 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Oracle In-Memory: Extreme Availability  Pure In-Memory format does not change  Oracle’s  storage format, logging, backup, recovery, etc.  All  Oracle’s  mature availability technologies work transparently  Protection from all failures  Node, site, corruption, human error, etc. RAC ASM RMAN Data Guard & GoldenGate
  16. 16. 16 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Oracle In-Memory: Unique Fault Tolerance  Similar to storage mirroring  Duplicate in-memory columns on another node • Enabled per table/partition • Application transparent  Downtime eliminated by using duplicate after failure
  17. 17. 17 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Oracle In-Memory: Implement in Minutes 1. Configure Memory Capacity  inmemory_size = XXX GB 2. Configure tables or partitions to be in memory  alter  table  |  partition    …    inmemory; 3. Drop analytic indexes to speed up OLTP
  18. 18. 18 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Oracle In-Memory Requires Zero Application Changes Full Functionality - No restrictions on SQL Easy to Implement - No migration of data Fully Compatible - All existing applications run unchanged Fully Multitenant - Oracle In-Memory is Cloud Ready Uniquely Achieves All In-Memory Benefits With No Application Changes
  19. 19. 19 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Oracle Applications From Batch to Real-Time With In-Memory and Engineered Systems Oracle Database In-Memory Oracle Applications
  20. 20. 20 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Real-Time Enterprise  Data Driven – Rapidly make decisions based on real-time data  Agile – Respond quickly to change  Efficient – Continually improve processes and profitability Real-Time Enterprise AGI LE EFFICIENT DATA- DRIVEN AGILE
  21. 21. 21 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Oracle In-Memory Cost Management  Adjust product mix, pricing, and marketing investments to maximize profits in real-time  Recalculate cost of every component in inventory, work-in-process, in-transit shipments, and finished good  Fast analysis of cost differences across manufacturing locations for make or buy decisions • 1.9 Billion Cost Rows • 13.8 Million Items • 14 Level BOM From 58 Hours to 13.5 Minutes 257X Faster
  22. 22. 22 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. PeopleSoft In-Memory Financial Analyzer  Iterative financial position analysis in real-time  Make earlier decisions for the financial period  Speed account reconciliation  Shorten financial period close • 290M Ledger Lines • 250 Business Units • 7 Step Analysis, Pivot, Drill From 4.3 Hours to 11.5 Sec 1300X Faster
  23. 23. 23 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Oracle In-Memory Transportation Management  Dispatchers perform real-time monitoring and rerouting when en-route exceptions occur  Benefits of instant rerouting:  Reduction in empty miles and in Driver turnaround time  Improved on-time delivery  Improved Dispatcher efficiency and Driver retention • 145M Status Records • 60M Shipment Data Records • 16K Drivers From 16 Min to Sub-second 1030X Faster
  24. 24. 24 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. JD Edwards Sales Order Analysis  Operational Analysis of sales orders in real-time  Find immediate answers to unanticipated customer sales questions  Eliminate batch jobs, data exports, third-party systems  1000’s  of  use  cases  across  all   functional areas • 104 million sales order lines From 22.5 Min to Sub-second 1700X Faster
  25. 25. 25 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. JD Edwards Customer Receivables Management  Real-Time receivables summarization  Balances by customer, line of business, and currency  Eliminate multiple queries, batch jobs, data exports  Similar use cases for projects, suppliers, assets, inventory etc. • 10 million invoice lines From 244 Min to 4 Secs 3500X Faster
  26. 26. 26 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Oracle Value Chain Planning Demantra Promotion Planning  Marketing Managers want detailed data when analyzing promotion plans  Benefits of real-time promotion analytics:  Analyze promotion profit and revenue on real-time basis  Optimize promotion spend  Better assess timing and cost impacts • 1.3 Billion Rows • Aggregate 36M rows • 2 week major sell-through report From 1120 to 11 Seconds 102X Faster
  27. 27. 27 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Oracle Value Chain Planning Demantra Consumption Driven Planning  Daily store-level forecasting and replenishment requires processing high volume POS data multiple times a day  Benefits of real-time planning:  Consumption and shipment based forecasting in a single scalable system  Improved forecast accuracy and customer service levels at lower cost • 400 Million Rows • 1.4 Million SKU Locations From 12.7 Hours to 56 Minutes 13.5X Faster
  28. 28. 28 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Oracle Value Chain Planning Supply Chain Planning and Analytics  Supply Chain analysts spend hours processing granular supply and demand data  Benefits of real-time planning:  Planners share business metrics with analysts  and  VP’s  of  Supply  Chain  real- time  Quickly solve supply disruptions and unexpected demand fluctuations • 360K Items • 1.2M Demands, 1M exceptions • 5.7M KPI records From 230 to 3 minutes 76X Faster
  29. 29. 29 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Siebel Marketing – List Import  Real-time marketing for large numbers of prospects  Rapid processing of marketing data for campaign launch  Accelerate import of large numbers of prospects  Reduce data-cleansing time From 1.9 hours to 49 sec • Import and Cleanse 1 Million Records 140X Faster
  30. 30. 30 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Oracle Fusion Cloud Financials Subledger Period Close Exceptions  Lists all accounting events and journal entries that fail period close validation in real-time  Report is run many times at end of quarter and is a bottleneck to close From 10 Minutes to 3 Sec • 19 Million Ledger Lines 210X Faster
  31. 31. 31 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Oracle Fusion Cloud Financials Sales Pipeline Analytic Report • Report potential income in real-time • Aggregate revenue from opportunities grouped within each sales stage for a specific time period From 52 Minutes to 24 Sec • 1.6 million opportunities • 5.1 million revenue lines 129X Faster
  32. 32. 32 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Become a Real-Time Enterprise Using Oracle Database In-Memory Real-Time Enterprise  Data-Driven • Get immediate answers to any question with real-time analytics  Agile • Eliminate latency with analytics directly on OLTP data  Efficient • Non-disruptively accelerate all applications AGI LE EFFICIENT DATA- DRIVEN AGILE
  33. 33. 33 Copyright © 2014, Oracle and/or its affiliates. All rights reserved. Summary: Oracle Database In-Memory  Extreme Performance: Analytics & OLTP  Extreme Scale-Out & Scale-Up  Extreme Availability  Extreme Simplicity Powering the Real-Time Enterprise All In-Memory Benefits With No Application Changes
  34. 34. 34 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.

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