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Databases

What is eventual consistency and why should you care about it?

Distributed systems have unlocked high performance at a large scale and low latency. You can run your applications worldwide from the comfort of your Amazon Web Services (AWS) platform in California, but the user adding an item to their shopping cart in Japan will not notice any delay or system faults. However, distributed systems - and specifically distributed database systems - also malfunction.

Benchmarking Redis with k6

Previously, I have covered an article on Load Testing SQL Databases with k6 . For your information, from k6 version 0.29.0 onwards, you can write a k6 Go extension and build your own k6 binaries. This comes in handy as you can use a single framework for load testing different protocols, such as ZMTQ, SQL, Avro, MLLP, etc. In this series of k6 extensions, let’s benchmark Redis now.

Securing Your SQL Server Application: Enabling Client-Initiated Encrypted Connections

In the previous article we discussed how to enable a server initiated encrypted connection to a Microsoft SQL Server. But what if we have a scenario where we do not want to incur the overhead of encryption for every application? In that scenario instead of configuring the server to force encryption we will instead need the client to initiate the encrypted connection.

How to Implement Change Data Capture in SQL Server

Every organization wants to stay on the cutting edge of technology, making smart and data-driven decisions. However, ensuring that company information and data integration remains up to date can be a very time-consuming process. That is where CDC can make all the difference. Change data capture or CDC allows for real-time data set changes, ensuring that company data is always up to date. Change data capture can transform the way companies make data-driven decisions.