Oracle Coherence: in-memory datagrid
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Why is there the need of a datagrid? When? What is Oracle Coherence? What can it help you in order to scale your webapp?
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Oracle Coherence: in-memory datagrid
- 1. Oracle Coherence In-Memory Data Grid Emiliano Pecis Principal Sales Consultant <Insert Picture Here>
- 3. the need of a datagrid
- 4. Business Innovation Poses Extreme Challenges to Transactional Applications
- 7. WOA: good but unpredictable Client side Server side
- 12. Oracle Coherence: Data Grid Uses Caching Applications request data from the Data Grid rather than backend data sources Analytics Applications ask the Data Grid questions from simple queries to advanced scenario modeling Transactions Data Grid acts as a transactional System of Record, hosting data and business logic Events Automated processing based on event
- 20. Features : Observable Interface
- 21. Features : QueryMap Interface
- 22. Features : InvocableMap Interface
- 33. Betfair …. Bets on XTP Database Tier PL/SQL Stored Procedures Oracle DB Sun Solaris Oracle Coherence Linux Clustered Data Cache Application Logic JBoss Linux Application and Caching Tier User Tier Online Bettors/Gamblers Third-Party Applications The Internet
- 34. Sun’s use case 1/4
- 35. Sun’s use case 2/4
- 36. Sun’s use case 3/4
- 37. Sun’s use case 4/4
- 38. Summary and demo
- 41. Demo
- 42. Q & A
Notes de l'éditeur
- AGENDA Web 2.0 and Enterprise 2.0 Challenges and Solutions for Enterprise 2.0 Oracle’s Strategy for Enterprise 2.0
- Action Item: Organizations depending on the TP application style to support their businesses should anticipate a dramatic change in their application architecture and technology infrastructures as a consequence of greater demand in terms of scalability, performance and availability . Improvements in hardware and network speed, mature middleware platforms, and real-time-oriented application architectures have enabled the notion of the real-time enterprise (RTE). This is a technology-enabled business concept by which organizations exploit real-time access to data to run core business processes. An RTE's competitive advantage is its ability to respond faster than competitors to business events. This concept can be used to optimize business models and enable new business scenarios, such as convergent networks in telecommunications or automated trading in financial services. The RTE can be deployed by specific applications, such as &quot;microcommerce &quot; and &quot;micropayment &quot; systems, global-class business-to-consumer (B2C) applications, real-time monitoring and management, real-time fraud detection, and real-time risk management. These applications are often transactional, although different from traditional transaction processing (TP) systems in their architectures. Typically positioned at the high end of the TP spectrum in performance and scalability needs, they're usually highly business-critical and have to deal with sensitive information. Therefore, they are also characterized by high-end requirements in terms of availability, security and monitoring/management. As a consequence, the most-high-end TP scenarios will be more common, and even the most extreme will enter mainstream adoption .
- Today’s Application infrastructures are facing great demands in terms of service levels, scalability, flexibility. At the same time, hardware is commoditized yet increasingly powerful and capable to meet challenges. In order to turn challenges into opportunities for “future-proofing” environments, enterprises are “rethinking” their application infrastructures.
- Data Grids provide key data juncture between disparate applications and disparate data sources. Designed for reliability: withstand faults, outages Built to scale out as needed and handle load gracefully
- Data Grids are used for different purposes. These are the four most common uses. Caching Coherence was the first technology to proved reliable distributed caching Helped many organizations alleviate data bottleneck issues and scale out application tier Analytics Enables applications to efficiently run queries across entire data grid Support for heavy query loads, while improving responsiveness of each query Server failures do not impact correctness of “in flight” queries and analytics Transactions Data Grid provides optimal platform for joining data and business logic Greater business agility by moving database stored procedures into the Data Grid Coherence reliability allows not only in-memory data processing, but provides the ability to commit transactions in-memory Reliability is key to conducting in-memory transactions. Coherence provides absolute reliability – every transaction matters. Events Oracle Coherence Data Grid manages processing state, guaranteeing once-and-only-once event processing Data Grid provides scalable management of event processing
- Distributed data management: single system image Consensus: nodes know who is a member, state of cluster Shared responsibilities, holding data, backups, diagnostics No interruptions in the event of a server failure First Build: Objects are distributed in memory among different JVMs on different Servers. Objects are held in primary format in only one place of the grid. A backup of the same data is also held in the memory on a different server. So from applications perspective, it just asks for the data to the Coherence grid and Coherence fetches it. Even if the primary server where the object was held is not available, it knows where to get the back up and get the data. Second Build: At the heart of Coherence is a consensus among the Coherence servers regarding which servers are currently participating in the Coherence grid. The logic behind this consensus is built into each one of the Coherence servers. The consensus is maintained automatically as servers are added or go down or are removed from the grid. Third Build
- IBM shop Un unico shopping chart su 4 retail site
- Betfair is the world's leading online betting exchange, a concept it has pioneered since 2000 Betfair processes 5 million transactions a day and more than 300 bets a second . Betfair is a profitable and debt-free company, with annual revenue exceeding £180 million . Betfair deals a growing transactional workload (greater than 500 updates and thousands of inquiry transactions per second) with 24/365 availability requirements across geographically distributed data centers (Betfair has a data center in Australia as mandated by local laws). The initial online betting exchange system was an ASP.NET/Oracle application that was replaced in 2004 by a second-generation system (Betex ), which used the existing Oracle DB but replaced the ASP front end with a Java/JSP application (built on the JBoss open-source application server) that leveraged the Oracle Coherence (then Tangosol Coherence) distributed caching platform The architecture proved very scalable and has supported the company's growth since its implementation. However, to meet ongoing scaling demands and enable an order of magnitude increase in workload, Betfair is developing the &quot;Flywheel&quot; third generation of its platform , which will be based on a revolutionary event-driven architecture foundation.
- Customers should consider these requirements when looking at different solutions Most solutions add reliability on as an after-thought, Coherence was designed and built from the ground-up with reliability in mind Needs to be simple enough for corporate developers to easily adopt and integrate into existing applications
- That is why the Oracle Enterprise 2.0 platform, that combine with all the different solutions and technologies that we have talked about today, really define and form a complete solution set that is designed to be uptaken granularly and modularly. This gradual evolution allows the new E20 capabilities to leverage and use those infrastructure and application investments that have already been made, and thereby maximize them. In this way, the triumvirate of users, information, and systems experiences maximized interaction, efficiency and, ultimately, evolution.