Redis
Redis is an open-source, in-memory data-structure store that provides network-accessible data operations and supports persistence.
Amazon Web Services in Action, Third Edition: An in-depth guide to AWS
Redis is an in-memory data structure server that provides persistent and non-persistent key-value data storage and access.
- How it is used
- Uses Redis as a fast caching and working-data layer for web applications alongside a primary relational database.
- How deep it goes
- Works through deployment choices, a minimal CloudFormation cluster, access controls, and application use rather than Redis engine internals.
- Examples
- Shows a game leaderboard, a single-node CloudFormation cluster, and a Discourse forum using Redis with PostgreSQL.
- What you can do after
- Operate/configure it through ElastiCache deployment and access choices, then monitor its role in an application.
Read how Amazon Web Services in Action, Third Edition: An in-depth guide to AWS explains Redis →
Generative AI in Action
Redis is an open-source in-memory data store that supports key-value storage and multiple data structures for database, caching, and messaging workloads.
- How it is used
- Uses Redis as the searchable embedding store for a RAG chat application over blog posts.
- How deep it goes
- Works through local deployment, index fields, and chat retrieval, while leaving Docker installation outside scope.
- Examples
- Uses an RSS-fed blog index and a chat application that retrieves five matching chunks for a question.
- What you can do after
- Apply it via Redis Stack and Python to index post embeddings and retrieve context for RAG answers.
The Quick Python Book, Fourth Edition
Redis is an in-memory data-structure server that provides network-accessible key-value storage and related operations.
- How it is used
- Supports fast network-accessible storage for caching, message brokering, counters, lists, and quick lookups.
- How deep it goes
- Demonstrates Python connections, key-value operations, counters, lists, indexing, and expiration without exploring Redis internals.
- Examples
- Uses Python snippets for keys, strings, counters, lists, indexed reads, connection settings, and expiring values.
- What you can do after
- Operate Redis through redis-py by connecting to a server and performing key-value, counter, list, and expiration operations.
Read how The Quick Python Book, Fourth Edition explains Redis →
Road to Kubernetes
Redis is an open-source in-memory data structure store that can provide database, cache, and messaging functionality.
- How it is used
- Deploys Redis beside Python applications in Docker Compose and as a stateful Kubernetes workload.
- How deep it goes
- Demonstrates service definitions, client tooling, persistence, namespaces, StatefulSets, volume claims, and Services without exploring Redis-specific technical differences.
- Examples
- Uses redis-tools, a Compose redis service, named volumes, an rk8s-redis Namespace, and Redis Kubernetes manifests.
- What you can do after
- Operate/configure Redis with Docker Compose or Kubernetes, preserving data and connecting application services through declared endpoints.
Learn Docker in a Month of Lunches, Second Edition
Redis is an open-source in-memory data structure store that can function as a database, cache, and message broker.
- How it is used
- Decouples application components with asynchronous messaging to improve performance, scalability, and feature delivery without direct connections.
- How deep it goes
- Demonstrates container setup, publishing, subscribing, and protocol rationale, but does not detail Redis database or cache operations.
- Examples
- Uses Docker containers, Redis CLI commands, channel21, and repeated ping messages to demonstrate publishing and subscription.
- What you can do after
- Operate/configure Redis in Docker, publish messages with the Redis CLI, and verify delivery through a subscriber.
Read how Learn Docker in a Month of Lunches, Second Edition explains Redis →
Building Distributed Applications that Work
Redis is an in-memory data structure store commonly used as a database, cache, and message broker.
- How it is used
- Supports caching and locking in applications hosted by Aspire.
- How deep it goes
- Describes adding dependencies to an Aspire host, without detailing Redis configuration or behavior.
- Examples
- Uses an Aspire host configured to run a Redis component for caching and locking.
- What you can do after
- Configure an Aspire host to run a Redis component by adding the necessary dependencies.
Read how Building Distributed Applications that Work explains Redis →
Related concepts
- key-value storekind of · A key-value store is a data-storage system that associates keys with values and supports storing, retrieving, or updating values by key.
- Dapr componentused by · A Dapr component is a configurable, pluggable implementation that backs a Dapr API capability with an external service or infrastructure mechanism.
- distributed cachingused by · Distributed caching is a technique for storing reusable data in a cache shared across multiple networked processes, servers, or nodes.
- cachinguses · Caching is the practice of storing reusable data or computation results so later access can avoid repeating retrieval or computation.
These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.