Write Through Cache

Write-Through & Write-Behind Cache: An Introduction

With the increase in high traffic applications, the need for high performance is also increasing. Hence, distributed caching is used to improve application performance and scalability. Moreover, since the cache is in-memory, it is also much faster than the database, making caching a popular approach. Mostly, when using caching, every time the application adds the…

Distributed Caching in .NET: A Quick Overview

These days many businesses require processing extreme transactional and reference data during peak times, like banks processing customer transactions during holidays. However, a big challenge is to process data without hampering your application’s performance. Generally, application tiers are linearly scalable but databases are not. Hence, high transactional loads can result in database bottleneck and affect…

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Fixing Four ASP.NET Performance Bottlenecks

ASP.NET has become developers’ foremost choice in developing high traffic web applications. Because of its scalable nature, ASP.NET application tier can seamlessly handle thousands of concurrent users with their millions of requests per day. Such high traffic ASP.NET applications are deployed in a load balanced web farm with a load balancer routing user requests to…

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How to Optimize ASP.NET Core Performance with Distributed Cache?

ASP.NET Core is starting to become popular for developing web applications because of its cleaner and lighter architecture and cross platform support. And, many of these ASP.NET Core applications are high traffic and run in a load-balanced multi-server deployment. In fact, it’s very common to see 10-20 server web farms and some are much larger…

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How is a .NET Distributed Cache Superior to Key Value Store?

ASP.NET web applications, .NET web services applications, and other .NET server applications need to handle extreme transaction loads without slowing down. And, although their application tier scales linearly, the data storage and database tier does not scale and therefore becomes a bottleneck. As a result, the entire application cannot scale. Originally, simple in-memory distributed key-value…