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Sybase Adaptive Server Enterprise Product Direction Jan Gipe – IPG Product Mgmt [email protected] Agenda. ASE Scorecard ASE Overview and Product Direction Competitive Advantages Replication Overview and Product Direction. Addressing customer needs

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Sybase adaptive server enterprise product direction jan gipe ipg product mgmt jgipe@sybase com

Sybase Adaptive Server EnterpriseProduct DirectionJan Gipe – IPG Product [email protected]


Agenda
Agenda

  • ASE Scorecard

  • ASE Overview and Product Direction

  • Competitive Advantages

  • Replication Overview and Product Direction


Ase scorecard

Addressing customer needs

Faster delivery of features utilizing in-market releases, 12.5.0.1 and 12.5.0.3, 12.5.1

Delivery of features that customers want (improved operational scalability, Linux support, DBXray visual diagnostic tool, LDAP authentication)

Working with partners

Working with Veritas on support for cluster solutions

Collaboration with HP around Itanium

New and improved tools with BMC and Lecco Tech– DB Expert, DBXray

Commitment to product

Continued investment to maintain leadership position in specific areas

Superior performance on 4-way Intel/Linux

Technology innovation

First to support XML natively in server; new support for Xquery and web services

Complete range of availability solutions, including new support for snapshot replication

Executing on 2 year roadmap to meet next round of customer requirements

ASE in Sybase’s strategic vision

ASE is a key component in Sybase’s strategic direction in Real-time services

Move from database to data management platform

ASE Scorecard


Enterprise data management today s it focus total cost of operations

Application Development

Rapidly Evolving Business Models

Multiple Development Options (XML, Java, SQL)

New Legislative Requirements

Data Management & Operations

Higher Data Availability

More Data Online

Growing Data Sizes

Platform & Infrastructure

Cost Pressures

Business Continuity

Scarcity of Skills

Time-to-Market

Budget

Enterprise Data ManagementToday’sIT Focus – Total Cost of Operations

Impacts on TCO:

Operational Constraints:


The operational gap

Storage & Access Volumes

Operational Capacity

Very Large

Operational

Gap

RDBMS

Large

Small

1980

2000

1990

The Operational Gap

More Data, More Transactions, Limited Resources


Sybase ase tco leader in enterprise data management
Sybase ASE TCO Leader in Enterprise Data Management

“Based on our analysis of thousands of applications,

the total life-cycle cost of most RDBMS applications will be, on average, more than 15 percent lower when running on Sybase ASE versus the equivalent offering from Oracle Corporation”

- Standish Group, 2003


Sybase ase inherent tco advantages
Sybase ASE Inherent TCO Advantages

Application

Development

Costs

20%

Web

Architecture

Service Oriented Architecture

Web Services

& XML

Database

Operational

Costs

Integrated Data

Delivery

60%

Self-

Management

Virtualized

Data Services

20%

Lower Cost Platforms

Provisioning

Grid Computing

ASE 12.5.1

Key Technologies

Future ASE

Technologies

TCO Components


Sybase ase 12 5 family overview
Sybase ASE 12.5 Family Overview

12.5.0.3

12.5.0.1

12.5

  • Security

    • Secure Sockets Layer

    • Row based access controls

  • Performance

    • New Page Sizes: 4K, 8K & 16K pages

    • Dynamic Tuning

  • Availability

    • Additional HA Cluster Support

    • Compressed Backups

    • Enhanced QuiesceDB

  • Application Development

    • Fast EJB’s

    • XML Indexing

    • Access to External File System

  • Availability

    • ASE Replicator (built-in Replication)

    • Enhanced HA

  • Migration

    • Migration Tools

  • Application Development

    • JVM & XML Enhancements

  • Administration

    • DB-Xray

    • Sampling based Statistics

  • Migration

    • PowerTransfer Migration Utility

  • Availability

    • Sun Clusters: Active/Passive


Sybase ase 12 5 1 design focus
Sybase ASE 12.5.1 – Design Focus

Higher Operational Scalability

Reduced Human Intervention

Lowering the Cost of

Applications

  • Simplified administration tasks

  • Simpler skill sets

  • Fewer user errors

  • Reduced planned downtime

Improved Developer Productivity

  • Reduced learning curve

  • Less coding

  • Easily expose data as a service

Improved System Performance

Lower Hardware Costs

  • More Throughput with Less H/W

    • Manage more data and transactions

    • Transition to Low Cost hardware while maintaining performance

Lowest

TCO


Sybase ase 12 5 1 design focus1
Sybase ASE 12.5.1 – Design Focus

Higher Operational Scalability

Reduced Human Intervention

Lowering the Cost of

Applications

  • Administration Improvements

  • DBA & Developer Tools

  • Self Management

  • Security & Availability

Improved Developer Productivity

  • Web Services Advancements

  • Enhanced XML

  • Derived Tables

  • Globalization Enhancements

Improved System Performance

Lower Hardware Costs

  • TempDB Enhancements

  • I/O Enhancements

  • Faster Maintenance Operations

  • Linux Performance

Lowest

TCO


Administration improvements

Transportable Databases

Quick copies for reporting or online backups

Ship pre-configured databases

Minimize downtime during application re-provisioning

Dynamic Cache Management

Reduces planned downtime and increases availability during application tuning

Simplified Installer

Easy configuration

Administration Improvements

Operational Scalability

Reduce Planned Downtime

Improve DBA Productivity


Tools for dbas and developers
Tools for DBAs and Developers

Operational Scalability

  • DBXray

    • Monitor server health & bottlenecks with drill down capabilities

  • DB Expert

    • Analyze, predict, optimize and manage database performance

  • SQL Expert

    • Tune application performance

DBXray

Improve Application Performance

DBExpert


Self management

Job Scheduler

Schedule consistency checks, index management and reports

Templated Backups –predefined templates for scheduling backups

Templated Resource Management – predefined templates to monitor and dynamically adjust resources like connections and locks

Automatic DB Space Management

Automatically grow databases and logs with thresholds

Reduced unplanned downtime with self healing

Automatic Garbage Collection

Cleanup unused space automatically

Self Management

Operational Scalability

Reduce Planned Downtime

Reduce Human Intervention


Security availability
Security & Availability

Operational Scalability

  • Simplified Security Administration

    • Centralized User Management through LDAP

    • Single Login/Password

  • Availability

    • Dynamic Listener Support

      • Add capacity on demand

      • Recover quickly from listener attacks

    • Enhanced Cluster support for highly available multi-node configurations

      • Sun Cluster 3.0, Veritas VCS 3.5

Login

Authenticate

LDAP Server

Improve Application Availability


Tempdb enhancements reduce contention

Multiple TempDB

Reduced contention for tempdb by assigning applications or users to different tempdbs

Optimized TempDB Logging

Increased throughput with reduced log space contention

Optimized TempDB I/O

Performance of TempDB operations (select into) improved with optimized I/O

TempDB Enhancements: Reduce Contention

System Performance Improvement

% Contention

15

10

Contention on catalog

5

0

5

10

15

20

25

Number of clients

1 Temp DB

2 Temp DB

Higher Throughput

Higher Application Performance


I o enhancements

Select Into Enhancements

Optimized Logging reduces the number of I/O Operations

Use of large memory buffers reduce the number of I/O Operations

Create/Load/Alter Database Enhancements

Significant increase in performance with the use of Large I/O buffers

Higher degree of Parallelism in operating on a single or multiple devices for these large operations

ASE 12.0

ASE 12.5.1

I/O Enhancements

System Performance Improvement

Create Database

12000

10000

8000

6000

4000

2000

0

Total Time

Higher Throughput

Higher Application Performance


Faster maintenance operations

Parallel Recovery

Faster Recovery at fail-over improves Availability

Reduces downtime for large environments

Parallel Check Points

Reduces Recovery Time through more frequent check points and more I/O at each check point

Sampling Based Statistics

Reduced maintenance time for updating statistics for very large data sets

Faster Maintenance Operations

System Performance Improvement

System Recovery Time

100

80

Recovery Time Percentage

60

40

20

0

1

2

3

Number of Recovery Tasks

Reduced Planned Downtime


High performance on linux
High Performance on Linux

System Performance Improvement

Sybase/HP joint performance benchmark results.

  • Best 1-4 CPU OLTP performance

  • Best response time

  • Low resource requirement (4GB vs SQL Server 32GB memory)

System Recovery Time

70000

60000

50000

40000

30000

20000

10000

Trans/Min

0

1

2

3

4

Number of CPUs

4 2.0Ghz Intel Xeon processors and 4GB of memory on Proliant Systems


Support for open standards

XML Enhancements

XML Storage and Retrieval

Fast XML Indexes

XML-SQL Interoperability

XPATH and XQUERY

Web Services Support

ASE as a producer : Publish data as Web service

ASE Web Services Producer

Input: SOAP

Input: JDBC

Output: SOAP

Output: JDBC

Any SOAP client

ASE

Support for Open Standards

Lower Cost of Applications

Faster Application Development

Less Custom Code


Xml processing in ase today

Message Services

Web Services

RelationalData

Internal SQL Query

or

External XQuery

XML

Data

Translation to

Relational Form

XMLInput

XML Processing in ASE – Today

RelationalData

XMLOutput

  • Support both native handling and “shredding” of XML data

  • Performance enhancements and support for multi-document queries

  • XQUERY Support

    • Global indexing, providing enhanced query performance; upgrades to our Full-Text Search service to be more XML-aware, as well as optimal handling of the XQUERY syntax

  • Support for “for XML” clause that is SQLX complaint

    • Representation of SQL result sets in XML, including mappings for SQL names, datatypes, and values.

  • A new “XML” datatype for SQL


Xml support in ase today

Native XML Support

Store and Retrieve XML documents natively – Schema independent and dynamic

Patent pending fast XML Indexes (as efficient as B-Tree for relational data) – provides a very high performance for querying

Self Defined indexes – no user input necessary

SQL and XML duality

Complete interoperability between XML and SQL at the language and storage level

Select … from … FORXML will send the results in XML format

Select … Xmlparse(xmldoc) will parse the XML document

XPATH and XQUERY Support

Fully support XQUERY 1.0 and XPATH 2.0 standard

XQUERY/XPATH for querying XML data (like SQL for relational data)

Support wildcards and functions for complex querying

XML Views/Mapping & Transformation

Can easily map XML data as SQL and SQL data as XML

Can apply XML transformations to stored XML document as well as the XML view of the SQL data

XML Support in ASE – Today


Web services support in ase 12 5 1

Expose logic inside ASE as a Web Service

ASE as a Web Service Requestor/Orchestrator

Use ASE to access a Web Service and use the result along with other data

Expose logic inside ASE as a Web Service

Details

Access T-SQL (stored procedures, user defined functions) as web methods

Persistent database connections via sessions

Support SSL

RPC/encoded web services support Access T-SQL as web methods

Generate dynamic WSDL

ASE Web Services Producer

Input: SOAP

Input: JDBC

Output: SOAP

Output: JDBC

Any SOAP client

ASE

Web Services Support in ASE 12.5.1


Improved isv support globalization

Support for Derived Tables

Better support for ISV/VAR applications

Enhanced application portability to ASE platform

ANSI SQL 2002 Compliance

Unicode Enhancements

Enhanced support for applications dealing with global data

Chinese Character Set – GB18030 Support

Compliance with Chinese Regulations

Improved ISV support & Globalization

Lower Cost of Applications

Less Custom Code


Sybase ase 12 5 1 takes care of business
Sybase ASE 12.5.1Takes Care of Business

Sybase ASE is the most cost-effective data management platform for business-critical computing.

  • Operational Scalability – reducing costs of people, systems and time

  • System Performance – handling more data, transactions, and applications with existing resources

  • High Performance on Linux – lower cost platforms for business critical tasks

  • XML and Advanced Web Services – faster application development


Ase future roadmap 2004 2005
ASE Future Roadmap 2004-2005

Higher Operational Scalability

  • Self Management – Zero Admin

  • Security, Auditing & Archiving

  • Availability Clusters

  • VLDB Enhancements

  • Partitions

Improved System

Performance

  • New Optimizer

  • New Execution Engine

  • Scalability Clusters

Lowering the Cost of Applications

  • XQUERY Support

  • XML Transformations

  • Managed Services

  • Real Time Services

Lowest

TCO


Self management today and future

Job

Scheduler

Job

Scheduler

Resource

Management

Module

Resource

Management

Module

Self Management – Today and Future

Self Management

Subsystems

Polling

ASE

Object

Fault

Fault

Configuration

Event

Space

Dynamic

Configuration

Dynamic Configuration

ASE 12.5.1

Future ASE


Self management future directions

Event management

Deliver alerts triggered by system or user-defined events to Job Scheduler

Space management

Database shrink capability

Auto data de-fragmentation and re-org for data and index

Object management

Index usage/tracking across boots

Configuration management

Reduce number of configuration knobs

Heuristics for automatic growth and shrinkage of configuration values

Query tuning and optimizer performance

Auto update statistics

Self-learning, self-tuning optimizer

Fault management

Run data integrity checks when cycles are available to continue from last time

Eliminate faults that can be managed within ASE and schedule tasks to manage them

High availability

Indices made online as soon as rebuilt

Index reorg or other utilities do not block data access

Empirical monitoring & feedback system

Policy definition/enforcement

Self Management – Future Directions


Vldb enhancements future

Segment-based Partitions

Partitioned tables

Range, Hash partition support

Add/Drop one or more partitions

Clustered/Non-Clustered Indexes

Global and local indexes on partitions

Update statistics on one or all partitions

Truncate partition

Optimizer and Execution support for partitioned tables

New Limits

More than 256 devices

More than 32 segments

Remove 30 char limit on names

Object Level Recovery

Recover database objects from database dumps

Make database consistency checks an offline activity

Row locked system catalogs

VLDB Enhancements – Future


Improved system performance new optimizer
Improved System PerformanceNew Optimizer

Efficient Query Optimization


New platform benchmark results
New Platform: Benchmark Results

Execution Time

I/O Count

Query 1 Query 2 Query 3

Query 1 Query 2 Query 3

Database size – 630 MB

Query 1: Join with expressions and no indexes (infinite improvement)

Query 2: Vector aggregation with Group By (exec time improvement – 186%; I/O savings – 83%)

Query 3: Multiple scalar aggregation (exec time improvement – 571%; I/O savings – 93%)


Sybase cluster solutions current 2 node active active ase solution

HA System

Establish Companion

Node2

Node1

ASE1

ASE2

Shared Disk Storage

Replicate

Users/Logins

Disk

Disk

Sybase Cluster Solutions - Current2-Node Active/Active ASE Solution

  • Although the disk is available to both nodes, the databases are not shared by the nodes – only at failure time are the disks from the failed node accessed by the companion node

  • 2 Node Cluster Solutions

    • Each node is a fail-over candidate for the other node

    • Both nodes run can active applications


Sybase cluster solutions current active passive multi node solutions
Sybase Cluster Solutions – CurrentActive/Passive, Multi-node Solutions

  • Multi-Node Cluster Solutions

    • Multiple nodes are joined in a cluster, eg., Egenera Bladeframe systems

    • N+1 Node Cluster Availability

    • Typically, one node is passive and is designated the fail-over candidate for any of the other nodes

    • Protects against a single failure among N+1 nodes

  • Cluster software mechanisms also provide multi-node (Active/Passive configuration) availability

    • Cluster software detects failure of an active node and fails over ASE and disks to the fail-over candidate as configured previously (ASE server instance is started on the fail-over node)

Cluster Software

Active Nodes

Passive Node

Shared Disk System


Availability clusters
Availability Clusters

  • N Node Cluster Availability

    • All nodes may run applications (some may be intentionally left idle to ensure service levels after failures)

    • Any node is a fail-over candidate for any of the other nodes

    • Protects against multiple failures As mission critical systems cannot tolerate even a few minutes or seconds of latency at fail-over time (typically required for recovery of the failed databases), a new approach is required

  • Each node in the cluster will run an Active ASE Server instance

    • The databases and disks are accessible *and* available to each ASE server instance (the databases are essentially shared by all nodes)

  • When one of the nodes fail, any of the other nodes can seamlessly takeover the databases of the failed node

    • Since each database is always available to all the nodes, no recovery needs to be performed on the database at fail-over time

  • Sybase’s future solution for availability will provide near-instantaneous fail-over with minimal latency and downtime

    • Initially focused on 2-4 node clusters, will be enhanced to larger number of nodes in the future


Availability clusters future

Shared Disk System

Availability Clusters – Future

  • As the disks and databases are shared among the nodes, client applications can be migrated to any node seamlessly and continue processing


Clusters for scalability
Clusters for Scalability

  • To achieve true scalability across a number of nodes, the application or data needs to be partitioned or mirrored on multiple nodes

  • Application Aware Partitioning

    • Data is partitioned across independent database servers and disks

    • Each server instance is completely independent and unaware of other data partitions

    • Client Application (or the mid-tier application server) is aware of the partitioning and directs the query/transaction to the corresponding node/server instance

    • If a query or transaction needs to access data on multiple nodes, the mid-tier application server coordinates the distribution among the nodes and the subsequent join of the results

    • While it imposes very few requirements on the DBMS, this solution suffers increases application development complexity


Clusters for scalability1

DB = Union(DB_Part_1, DB_Part_2, DB_Part_3, DB_Part_4)

Shared Disk System

DB_Part_3

DB_Part_1

DB_Part_2

DB_Part_4

Clusters for Scalability

  • Sybase will extend the continuous availability solution and the partition solution to provide cluster aware partition functionality

  • Data can be partitioned onto multiple nodes, but all partitions are accessible and available to all nodes via a shared disk system

    • Optimally, client applications are processed by the node that owns the partition required by the client application

    • However, in case of a failure, one or more of the remaining nodes seamlessly take over the partition(s) on the failed node to continue processing

  • Provides scalability and availability in a single solution


Security archiving
Security & Archiving

  • Encryption

    • Native Column-level Encryption in the Database

  • Auditing

    • Common Audit Repository

    • Enhancements to syb_audit functionality

    • Log Based or Sniffer based auditing

  • Archiving

    • Dynamic Archiving & Active Archiving


Future xml direction

XML Engine Enhancements

Multi Row (Multi Document) Index

XML Schema support

XML Data Type

XQUERY

Support for full XQUERY syntax

User defined XQUERY functions

XQUERY update syntax support

XQUERY caches for efficiency

Optimizer better tuned for XQUERY

XML Transformation Enhancements

SQLX scalar functions (XMLELEMENT etc.,)

Cursor (row-by-row) mapping for SQL to SQLX

SQLX mapping for SQL schemas and catalogs

Tighter integration with Jallora

Future XML Direction


Ase real time services today future
ASE Real Time Services – Today & Future

Power PocketBuilderApplication Development

RepConnector

ASE

XML

MobileAvantGo

3rd Party

ASE Real Time Services

Active Event

Publisher

Message Collector

Message Bus (TIBCO JMS, RV, MQ)



Ase roadmap
ASE Roadmap

Self Management

& Data Mgmt Services

Clusters & VLDB

Low TCO

  • ASE Future

  • Clusters

  • Partitions

  • Real-time Analytics

  • Self Management (Phase 3)

  • Security – Native Encryption

  • ASE 12.5.x

  • Self Management (Phase 2)

  • Real Time Services

  • Federated Computing

  • Security – Auditing

  • XML – XQUERY

  • Dynamic Archiving

  • ASE 12.5.1

  • Operational Scalability

  • Self Management

  • XML Performance & Transformations

  • Security – Authentication

  • Web Services

2004

2005

2006


Sybase ase performance innovation at lower cost
Sybase ASEPerformance, Innovation at Lower Cost

Most Successful Database Software Company in China

-CCID Consulting

ASE 15% lower TCO than Oracle

- Standish Group

“Sybase on Linux provides the stability, performance, and availability we need to keep our customers satisfied and our costs down.”

- Iroquois Gas

#1 in XML Storage Capabilities

- ZapThink


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