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Main Memory Caching Database

Target Audience: Product and Solution Architects

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Database Requirements for Telecom

Predictive Response Time

High Throughput

High Availability

High Concurrency

Distributed

Small Footprint

Solution: Main Memory Database (MMDB)

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Typical Real Time Telecom Applications

Soft switch : Call handling, Routing, Forwarding , Waiting, etc

Billing : prepaid, postpaid, rating

Management: EMS, NMS, AAA, Policy, Fraud

IN : HLR, VLR, Preference, Presence, Mediation

VAS : SMS (SMSC, Gateway, etc) Location Services CRBT Profile Based Services

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Telecom Companies using MMDB

Soft Switch Alcatel-Lucent, Cisco, Sonus Networks, TeraBridge

Billing Amdocs, Ushacomm

IN Alcatel-Lucent, Nokia Networks, Broadsoft

VAS Alcatel-Lucent

Management IBM-Micromuse, Caspian Networks

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CSQL MMDB– Feature Overview

Small footprint (less than 2 MB)

Real time predictive response Less than 10 microseconds always for point lookup Highly concurrent (uses lock free data structures) No disk I/O and network latency

High Throughput 100K selects/sec and 50K updates/sec

Standard Interface JDBC, ODBC, SQL

Access Modes Embedded, Client/Server

Supported Platforms Linux – x86, x86_64 Solaris – sparc, x86

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CSQL Replication

High availability Sub-Second fail over

Load Balancing with multiple distributed data nodes Multiple modes to support Read intensive and write intensive

applications

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CSQL Cache– For Existing Applications

Cache frequently accessed tables from existing(target) database close to application

Uses CSQL MMDB for cache

Unified Gateway Transparent access to tables,procedures residing in existing

database

Automatic Fail over to target database and recovery

Supported Database Platforms Oracle, Sybase, DB2, MySQL and Postgres

Predictive Response

10 microsecs select

High Throughput

100 times faster

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CSQL Cache Cluster

Load Balancing with multiple nodes Multiple modes to support Read intensive and write intensive

applications

Cache Granularity

Full Table

Partial Columns

Partial Records

Updateable cache

Transactions on cache propagates to centralized database and vice versa

Transaction Propagation Modes

Synchronous, Asynchronous

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Wisconsin Benchmark ResultsMachine Configuration

Dell Optiplex 320, Intel core 2 duo @2.0 GHz, with 1GB RAM on Linux 2.6 Kernel

Wisconsin benchmark tables with 10K records using JDBC Leading DB (tables fully loaded in memory) All statements retrieves one record except “select-100” which retrieves

100 records

Statement Type NoIndexHash Index

Tree Index NoIndex

Hash Index

Tree Index NoIndex

Hash Index

Tree Index

SelectInt -1 6097 331 325 247 11 11 24.68 30.09 29.55SelectStr-1 6495 979 356 286 16 15 22.71 61.19 23.73Select-100 6861 NA 826 508 NA 68 13.51 NA 12.15Insert – 1 218 265 213 20 13 11 10.90 20.38 19.36Update -1 5572 217 188 473 14 12 11.78 15.50 15.67Delete-1 5741 200 168 573 15 13 10.02 13.33 12.92Join (10K * 1K) -1 6459 320 292 35 11 11 184.54 29.09 26.55Join (10K * 10K) - 1 14916 411 320 36 13 14 414.33 31.62 22.86

Leading DRDB CSQL MMDB Times Faster

All time in microseconds

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CSQL BenefitsTime to market

Standard ODBC and JDBC supportNo Application and Data Migration required for existing applicationsProfessional support for development and deployment

Increase RevenueScale to handle more subscribers, more calls

Lower TCOReduce licensing, support costs by more than 50%

Lower operating costsLess additional H/W for scaling

Improve Customer retentionNo dropped callsImprove QoS

More Information: http://www.csqldb.comContact: sales@csqldb.com