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Csql for telecom


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Csql for telecom

  1. 1. © This document contains confidential and proprietary information of Lakshya. It is furnished for evaluation purposes only. Except with the express prior written permission of Lakshya, this document and the information contained herein may not be published, disclosed, or used for any other purpose. Main Memory Caching Database Target Audience: Product and Solution Architects
  2. 2. Database Requirements for Telecom <ul><li>Predictive Response Time </li></ul><ul><li>High Throughput </li></ul><ul><li>High Availability </li></ul><ul><li>High Concurrency </li></ul><ul><li>Distributed </li></ul><ul><li>Small Footprint </li></ul>Solution: Main Memory Database (MMDB)
  3. 3. Typical Real Time Telecom Applications <ul><li>Soft switch : Call handling, Routing, Forwarding , Waiting, etc </li></ul><ul><li>Billing : prepaid, postpaid, rating </li></ul><ul><li>Management: EMS, NMS, AAA, Policy, Fraud </li></ul><ul><li>IN : HLR, VLR, Preference, Presence, Mediation </li></ul><ul><li>VAS : </li></ul><ul><ul><li>SMS (SMSC, Gateway, etc) </li></ul></ul><ul><ul><li>Location Services </li></ul></ul><ul><ul><li>CRBT </li></ul></ul><ul><ul><li>Profile Based Services </li></ul></ul>
  4. 4. Telecom Companies using MMDB <ul><li>Soft Switch </li></ul><ul><ul><li>Alcatel-Lucent, Cisco, Sonus Networks, TeraBridge </li></ul></ul><ul><li>Billing </li></ul><ul><ul><li>Amdocs, Ushacomm </li></ul></ul><ul><li>IN </li></ul><ul><ul><li>Alcatel-Lucent, Nokia Networks, Broadsoft </li></ul></ul><ul><li>VAS </li></ul><ul><ul><li>Alcatel-Lucent </li></ul></ul><ul><li>Management </li></ul><ul><ul><li>IBM-Micromuse, Caspian Networks </li></ul></ul>
  5. 5. CSQL MMDB– Feature Overview <ul><li>Small footprint (less than 2 MB) </li></ul><ul><li>Real time predictive response </li></ul><ul><ul><li>Less than 10 microseconds always for point lookup </li></ul></ul><ul><ul><li>Highly concurrent (uses lock free data structures) </li></ul></ul><ul><ul><li>No disk I/O and network latency </li></ul></ul><ul><li>High Throughput </li></ul><ul><ul><li>100K selects/sec and 50K updates/sec </li></ul></ul><ul><li>Standard Interface </li></ul><ul><ul><li>JDBC, ODBC, SQL </li></ul></ul><ul><li>Access Modes </li></ul><ul><ul><li>Embedded, Client/Server </li></ul></ul><ul><li>Supported Platforms </li></ul><ul><ul><li>Linux – x86, x86_64 </li></ul></ul><ul><ul><li>Solaris – sparc, x86 </li></ul></ul>
  6. 6. CSQL Replication <ul><li>High availability </li></ul><ul><ul><li>Sub-Second fail over </li></ul></ul><ul><li>Load Balancing with multiple distributed data nodes </li></ul><ul><ul><li>Multiple modes to support Read intensive and write intensive applications </li></ul></ul>
  7. 7. CSQL Cache– For Existing Applications <ul><li>Cache frequently accessed tables from existing(target) database close to application </li></ul><ul><ul><li>Uses CSQL MMDB for cache </li></ul></ul><ul><li>Unified Gateway </li></ul><ul><ul><li>Transparent access to tables,procedures residing in existing database </li></ul></ul><ul><li>Automatic Fail over to target database and recovery </li></ul><ul><li>Supported Database Platforms </li></ul><ul><ul><li>Oracle, Sybase, DB2, MySQL and Postgres </li></ul></ul><ul><li>Predictive Response </li></ul><ul><ul><li>10 microsecs select </li></ul></ul><ul><li>High Throughput </li></ul><ul><ul><li>100 times faster </li></ul></ul>
  8. 8. CSQL Cache Cluster <ul><li>Load Balancing with multiple nodes </li></ul><ul><ul><li>Multiple modes to support Read intensive and write intensive applications </li></ul></ul><ul><li>Cache Granularity </li></ul><ul><ul><li>Full Table </li></ul></ul><ul><ul><li>Partial Columns </li></ul></ul><ul><ul><li>Partial Records </li></ul></ul><ul><li>Updateable cache </li></ul><ul><ul><li>Transactions on cache propagates to centralized database and vice versa </li></ul></ul><ul><li>Transaction Propagation Modes </li></ul><ul><ul><li>Synchronous, Asynchronous </li></ul></ul>
  9. 9. Wisconsin Benchmark Results <ul><li>Machine Configuration </li></ul><ul><ul><li>Dell Optiplex 320, Intel core 2 duo @2.0 GHz, with 1GB RAM on Linux 2.6 Kernel </li></ul></ul><ul><ul><li>Wisconsin benchmark tables with 10K records using JDBC </li></ul></ul><ul><ul><li>Leading DB (tables fully loaded in memory) </li></ul></ul><ul><ul><li>All statements retrieves one record except “select-100” which retrieves 100 records </li></ul></ul>All time in microseconds
  10. 10. CSQL Benefits <ul><li>Time to market </li></ul><ul><ul><li>Standard ODBC and JDBC support </li></ul></ul><ul><ul><li>No Application and Data Migration required for existing applications </li></ul></ul><ul><ul><li>Professional support for development and deployment </li></ul></ul><ul><li>Increase Revenue </li></ul><ul><ul><li>Scale to handle more subscribers, more calls </li></ul></ul><ul><li>Lower TCO </li></ul><ul><ul><li>Reduce licensing, support costs by more than 50% </li></ul></ul><ul><li>Lower operating costs </li></ul><ul><ul><li>Less additional H/W for scaling </li></ul></ul><ul><li>Improve Customer retention </li></ul><ul><ul><li>No dropped calls </li></ul></ul><ul><ul><li>Improve QoS </li></ul></ul>More Information: Contact: