Using the Redis NoSql database with .NET Part 3: lists in Redis

Introduction

In the previous post we first installed the Redis server as a Windows service. It’s cumbersome having to execute redis-server.exe every time we want to communicate with the database so we’ll have it running as a service. Then we went on to explore the string data type in Redis. String is the most versatile data type since we can store pretty much anything as a string in one way or another: messages like “Hello”, JSON serialised custom objects, base 64 encoded byte arrays for e.g. file content, numbers etc. We looked at a couple of string-related commands like STRLEN or APPEND.

In this post we will first add Redis to the environment variables so that we can reach the executables without navigating to the Redis folder in the command prompt. Then we’ll look at how lists are implemented in Redis.

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Using the Redis NoSql database with .NET Part 2: the Redis Windows service and some basic string commands

Introduction

In the previous post we introduced the topic of this series: Redis with .NET. We first went through some basic characteristics of Redis. It is a NoSql key-value store with in-memory storage and access by default. The records are stored by unique keys where each unique key has a value attached. It has many good features like fast data access, data replication, scripting, high-availability clusters, various data types and much more. Normally Redis is installed on Linux servers but we’ll go with the officially unsupported Windows 64-bit port maintained by Microsoft. That will fit most .NET developers out there who are the main target group of this series. We started the Redis server and client and tried three of the most basic Redis commands: GET, SET and DEL that vaguely correspond to SELECT, INSERT/UPDATE and DELETE statements in SQL.

In this post we will first install the Redis server as a Windows service and then test a couple of Redis commands related to strings.

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Using the Redis NoSql database with .NET Part 1: introduction and setup

Introduction

Traditional relational databases have received a couple of strong competitors in recent years. According to the db-engines website the 10 most widely used data stores are still dominated by relational databases and it will probably be the case for long years to come. However, there are many alternatives out there that can take their place in an application as its backing store. They can either act as the main data store of the application, i.e. where all the records are persisted for later retrieval. Alternatively they serve a different but very specific storage role that is not well suited for relational databases. In other words the application is backed up by e.g. SQL Server or MongoDb as its main data storage but delegates other storage needs, such as caching to say Memcached.

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