larry ellison introduces oracle database in-memory

Larry Ellison Chief Executive Officer, Oracle

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Oracle Database In-Memory Powering the Real-Time Enterprise

2 Copyright © 2014, Oracle and/or its affiliates. All rights reserved.

Oracle Database In-Memory

Option

Powering the Real-Time Enterprise

Available in July


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


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

SALES

REGIO

N


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

Analytics OLTP Sales Sales

Sales


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


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 Regionvalues V

ecto

r Re

gist

er

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

REGION


10x Faster Joining and Combining Data

Sales Stores

Type=outlet

Example: Find total sales in outlet stores

Storeid in

15,38,64 STOREID

AMOUNT

Converts join processing into fast column scans

Joins tables 10x faster

Sum

STOREID

TYPE


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

Out

lets

Footwear


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


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


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 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


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


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


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


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


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


Oracle Applications

From Batch to Real-Time

With In-Memory and Engineered Systems

Oracle Database In-Memory

Oracle Applications


Real-Time Enterprise

Data Driven – Rapidly make decisions based on real-time data

Agile – Respond quickly to change

Efficient – Continually improve processes and profitability


AGILE

EFFICIENT

DATA-DRIVEN AGILE


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


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


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


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


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


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


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


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


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


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


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


Become a Real-Time Enterprise Using Oracle Database In-Memory


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

AGILE

EFFICIENT

DATA-DRIVEN AGILE


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

larry ellison introduces oracle database in-memory

Technology

memory format

oracle andor

memory queries

memory report

memory speed

memory column format

memory option

memory powering