Oracle Coherence: performance, scalability and reliability in data management

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The rise of business sales being channelled through e-commerce portals poses new challenges in the field of information processing and analysis. In this context, database structuring and managing have become key to operating high-performance applications, such as search engines able to handle large volumes of data elements.

Challenges posed by these companies, go through the immediacy and reliability of data access in increasingly complex environments, simplifying information processing through intelligent analysis methods, and isolating original data source to prevent possible application failures.

System scalability must also be ensured to resolve problems associated with storage space required by databases.

Why do traditional databases fail to support critical applications?

On systems running high-performance applications (a search engine that must access large volumes of data) traditional databases provide heavier access times and procedures not comparable with cached structures as well as database access stress that can lead to system problems or failures.

An example:

Our business sells a large number of products through a web portal; when a user performs a query on our website, our search application will scan our extensive database looking for products relevant to the customer, using multiple criteria to be applied in search results.

Most likely the system will fail to handle the workload or respond slowly when accessed by multiple concurrent users coupled with complex search criteria.

In order to overcome limitations posed by a traditional databbase access system, we must isolate the original data source by means of data cache schemes.

How to improve performance and scalability of database systems?

Coherence is an Oracle solution that enables organizations to improve the performance of critical applications by means of fast, reliable access that is completely parameterisable to information used frequently.

Establishing data models in a Coherence grid structure we can execute and keep, in a controlled way, applications that require high-performance of systems and that must support complex searches.

A Coherence-based model enables us to extract a group of data from a traditional database in order to cache and host them in memories by means of grid structures (date matrices). This way, we derive complex operations carried out by applications (query, multiple search, data collection for complex calculations, etc.) from the original database to the Coherence grid, resulting in a much more efficient and fast process.

Establishing criteria for load and refreshment of cache data selection, we can then carry out searches within a reduced number of data, optimizing application performance.

Access time per data is substantially reduced by hosting data in RAM memory instead of on a disk.

On the other hand, with a Coherence-based model, we can define parameterization criteria related to fast searches, moving away from rigidity and limitation of PL (Procedural Language) language used in traditional data sources.

Coherence enables us to define hot data relations

Coherence cache data model enables us to establish processes that update data virtually the moment they are modified. That is, it is possible to set groups of data for which, in the event of amendments, a trigger will send that amendment to the Coherence grid with minimum latency.

This action enables us to move away from scheduled update processes (e.g. update of X data X times a day) as it occurs when working with PL. Consequently, we will have instant data updates for whatever is needed.

Additionally, Coherence own architecture can be distributed in different notes, being the Coherence solution the one in charge of keeping both integrity and coherence of information that must exist at all times in cache nodes.

At Innovation Strategies we specialize in cache conscious structure design with Oracle Coherence; we have helped many of our clients to speed up data consultation processes, therefore improving reliability, scalability and performance of critical data consuming systems related to high performance businesses.

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