Software Engineering :: Database :: Redis :: Training :: Courses :: Advanced Redis :: Introduction

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Software Engineering :: Database :: Redis :: Training :: Courses :: Advanced Redis :: Introduction

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redis

• Software Engineering :: Database :: Redis :: Solutions

An overview of Redis

Prerequisites

• Familiarity with the Redis data store
• Knowledge of the Redis CLI
• Understanding of Redis operations
• Proficiency in Python programming

Redis: An Open Source In-Memory Data Store for Databases, Caching, Streaming, and Messaging

In-memory Data Store: Redis Overview

Redis is a versatile in-memory data structure server capable of storing strings, numbers, lists, sets, sorted sets, and streams.

In-memory Data Store Overview

• Essential for building infrastructure for real-time applications.
• Supports streaming, messaging, caching, complex computations, and session state maintenance.
• Delivers extremely low latency and high throughput.

Core Redis Capabilities

• Programmability: Server-side scripting using Lua and stored procedures.
• Extensibility: Module API for custom extensions in C, C++, and Rust.
• Persistence: In-memory dataset for fast access, with options for permanent storage.

Core Redis Capabilities

• Clustering: Horizontal scaling with hash-based data sharding
• High Availability: Replication with automatic failover for standalone and clustered deployments

Course Topics Overview

• Pipelining
• Benchmarking
• RediSearch
• RedisJSON

Assumes basic familiarity and understanding of the Redis data store.

Optimizing Redis Interaction Through Pipelining

Key Focus: Minimize round trip times to the Redis server by efficiently batching commands.

Benchmarking Redis Operations Using Redis-Benchmark Utility

RediSearch: Enables Querying, Secondary Indexing, and Full-Text Search for Redis

RedisJSON: JSON Support for Redis - Store, Update, and Retrieve JSON Values

Redis Stack: Enhancing Core Redis with New Data Models and Tools

Redis Stack expands the functionality of the Redis store by introducing new data models, data processing capabilities, and debugging tools, including Pipelining, Benchmarking, RediSearch, and RedisJSON.

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