There were two key challenges which were addressed with a Coherence-based solution. One challenge is input data caching for the risk computation grid – pro-active caching based on Coherence has improved risk calculation time (by reducing data wait time) and allowed the risk grid to scale with yearly growing volumes. Another challenge is intraday risk – point-in-time aggregation based on Coherence reduced delay between data changes and risk updates.

Oracle Coherence improved site performance and the customer experience. Customers don’t want to see that the site is too slow or that there are breaks in transactions. They want faster access, especially for mobile devices. For people with network bandwidth and a data plan, it has to be faster.

We use Coherence in a range of applications, from business-critical applications dealing with a vast amount of fast-moving data, to smaller applications looking to share data efficiently internally and with external apps and businesses.

One example would be as a portion of a risk-calculation engine that calculates complex values like PV, VaR and Greeks. Other technologies don’t allow the same level of scale and compute capability, while providing rigorous resilience and security underpinnings.

It can handle an extremely high volume of data.

We implement ticketing analytics using Coherence.

This product helped our organization to focus on implementing business logic without worrying about scalability on user loads of huge data queries. Application latency improved drastically with the ability to scale with load.

Basically reducing response times to extremely small latencies in their apps.

Coherence has helped us to drastically reduce the request time of our web applications.

We are benefiting from performance, thanks to Extreme Performance and innovative architecture.

The project involved Java back end and Microsoft .NET front end. The product Portable Object Format (POF) allows the two platforms to exchange data seamlessly.

It decreased response times in B2B operations thanks to the grid calculations.

It has allowed us to greatly improve our response times in several services by caching part of the database into Coherence and executing complex queries using EntryProcessors.

The biggest improvement is in speed - everything is faster from record retrieval to workflow processing.

It has really transformed the speed that we can respond to customers. Now I don't need to worry about increasing my customer base. I used to wonder how I was really going to provide service to over five million customers. Generally, as the number of customers goes up, the biggest challenge is to provide the same kind of response time. Now I don't need to worry about it. I can just keep growing our customer base, but our response time tends to remain the same.

We are storing information from one of our applications. This allows us to answer requests in milliseconds, while the application would take seconds to answer request from clients.

An example of how the product improved organizational function was in the speed of request processing. The client had needs to support very high throughput, particularly at certain “peak” times of the year, both in terms of bandwidth for data streaming, as well as retail transactions. A robust standalone caching solution that prioritized speed of data serialization and data integrity was a must. Coherence delivered on that front.

The Customer Facing Application response time has been improved 95%. Also, in the releases the Portal does not goes down as the data is being pulled from the Cache not from the Database.

We were trying to get better performance of compute tasks previously developed on RDBMS to cache and it has improved the performance by a factor of 4.

I have worked on different projects that sometimes demand high performance (millions of transaction per day) without compromising availability or sequencing of the flows. Therefore, Oracle Coherence offered the possibility to cache and also allow sharing of cached objects through remote availability of the cache. Oracle Coherence is easy to integrate using any industry-based programming solution and standard products (works very effectively with Oracle middleware technologies). With Oracle Coherence, we managed to decouple many of our backend and legacy systems through limiting many incoming transactional requests and therefore improving performance immensely in such systems.

I am unable to name specific projects and companies for confidentiality reasons. I have, however, listed the high-level aspects of how Coherence benefited us.

For company X, a major telecom provider in the continental United States, we had the GRID edition here. A single logical cache scattered across various geographies ensured we had only one cache to look against (location transparency) at the same time, ensuring high availability. With Coherence taking care of CAP (Consistency, Availability and Partition Tolerance) we had little to worry about in those aspects. The ability to add any number of server instances and the ability to query with a simple API reaped benefits in our application scaling and the developers happy with the ease of coding.

The improvement on features of Tangosol Coherence during 2006 through 2009 was limited, but the best feature was the standalone. After 2013, integration with Oracle has added many features which have not been used much, or the industry is not ready for the features. It has become very heavy along with the price for Oracle's integrated product as a fusion middleware.

We are system integrators. We used Coherence in building a transaction processing system for a client. Introducing a data grid, we moved from a vertically scalable solution to full scalability. The data grid helped a lot to reach the goal of scaling the system in a virtualized environment.

Coherence has improved response times for queries of sizeable data sets. Also by allowing for data distribution and replication through clustering, it improves the reliability of information systems.

It helped us to cache the data in memory and improved performance by 10x.

It was suited for stock exchange marketing software, improved performance.

We used the distributed caching mechanism to keep the cache up-to-date with the database. Implementation of the Touch processor helped a lot.

By embedding Coherence and clustering the application, you can eliminate single source of failure problems. 

We use WebLogic as the JMS provider. For technical reasons, we were not successful in clustering it, so we have a single source of failure problem.