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Amazon RDS for Aurora vs Redis: What are the differences?

Introduction

Amazon RDS for Aurora and Redis are two popular database services provided by Amazon Web Services (AWS). While both offer high-performance and scalable solutions, there are several key differences between the two. This Markdown code will provide an overview of these differences in a concise and structured manner.

1. Scalability and Replication:

Amazon RDS for Aurora supports automatic scaling and replication. It can automatically create up to 15 read replicas to offload read traffic and improve performance. On the other hand, Redis supports replication, but it does not offer built-in automatic scaling. To handle increased traffic, additional Redis instances need to be manually provisioned.

2. Data Model:

Amazon RDS for Aurora is a relational database engine based on MySQL and PostgreSQL. It uses a traditional relational data model, supporting tables, rows, and SQL queries. Redis, on the other hand, is a NoSQL database engine that follows a key-value data model. It stores data as key-value pairs and offers advanced data structures like lists, sets, and hashes.

3. Durability and Availability:

Amazon RDS for Aurora provides high durability by storing six copies of data across multiple Availability Zones (AZs). It automatically replicates data to ensure availability in case of a failure. Redis, on the other hand, allows data persistence by periodically saving data to disk. While Redis can recover data after a failure, it is not as fault-tolerant as Amazon RDS for Aurora.

4. Caching Features:

Redis is often used as an in-memory cache due to its fast access times. It offers built-in caching features like eviction policies and expiration times for keys. Amazon RDS for Aurora does not have dedicated caching capabilities as it is primarily designed for storing and querying data in a relational manner.

5. Data Access Patterns:

Amazon RDS for Aurora is suitable for complex relational queries where structured data and SQL capabilities are required. It is a good choice for transactional workloads and applications that need ACID compliance. Redis, on the other hand, excels in scenarios that require high-performance data access, such as real-time analytics or caching.

6. Pricing and Cost:

The pricing model for Amazon RDS for Aurora and Redis differs based on various factors. Amazon RDS for Aurora has both instance-based and storage-based pricing, where users pay for the compute instances and storage they use. Redis has a simpler pricing structure based on the instance type and capacity. The overall cost depends on the specific requirements and usage patterns of the application.

In summary, Amazon RDS for Aurora provides automatic scaling and replication, follows a relational data model, offers high durability, lacks caching features, suits complex relational queries, and has a flexible pricing model. In contrast, Redis requires manual scaling, follows a key-value data model, has data persistence with limitations, offers powerful caching capabilities, suits high-performance data access, and has a simpler pricing structure.

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Pros of Amazon Aurora
Pros of Redis
  • 14
    MySQL compatibility
  • 12
    Better performance
  • 10
    Easy read scalability
  • 9
    Speed
  • 7
    Low latency read replica
  • 2
    High IOPS cost
  • 1
    Good cost performance
  • 886
    Performance
  • 542
    Super fast
  • 513
    Ease of use
  • 444
    In-memory cache
  • 324
    Advanced key-value cache
  • 194
    Open source
  • 182
    Easy to deploy
  • 164
    Stable
  • 155
    Free
  • 121
    Fast
  • 42
    High-Performance
  • 40
    High Availability
  • 35
    Data Structures
  • 32
    Very Scalable
  • 24
    Replication
  • 22
    Great community
  • 22
    Pub/Sub
  • 19
    "NoSQL" key-value data store
  • 16
    Hashes
  • 13
    Sets
  • 11
    Sorted Sets
  • 10
    NoSQL
  • 10
    Lists
  • 9
    Async replication
  • 9
    BSD licensed
  • 8
    Bitmaps
  • 8
    Integrates super easy with Sidekiq for Rails background
  • 7
    Keys with a limited time-to-live
  • 7
    Open Source
  • 6
    Lua scripting
  • 6
    Strings
  • 5
    Awesomeness for Free
  • 5
    Hyperloglogs
  • 4
    Transactions
  • 4
    Outstanding performance
  • 4
    Runs server side LUA
  • 4
    LRU eviction of keys
  • 4
    Feature Rich
  • 4
    Written in ANSI C
  • 4
    Networked
  • 3
    Data structure server
  • 3
    Performance & ease of use
  • 2
    Dont save data if no subscribers are found
  • 2
    Automatic failover
  • 2
    Easy to use
  • 2
    Temporarily kept on disk
  • 2
    Scalable
  • 2
    Existing Laravel Integration
  • 2
    Channels concept
  • 2
    Object [key/value] size each 500 MB
  • 2
    Simple

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Cons of Amazon Aurora
Cons of Redis
  • 2
    Vendor locking
  • 1
    Rigid schema
  • 15
    Cannot query objects directly
  • 3
    No secondary indexes for non-numeric data types
  • 1
    No WAL

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What is Amazon Aurora?

Amazon Aurora is a MySQL-compatible, relational database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. Amazon Aurora provides up to five times better performance than MySQL at a price point one tenth that of a commercial database while delivering similar performance and availability.

What is Redis?

Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.

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What are some alternatives to Amazon Aurora and Redis?
MySQL
The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
PostgreSQL
PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.
MongoDB
MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
Amazon S3
Amazon Simple Storage Service provides a fully redundant data storage infrastructure for storing and retrieving any amount of data, at any time, from anywhere on the web
GitHub Actions
It makes it easy to automate all your software workflows, now with world-class CI/CD. Build, test, and deploy your code right from GitHub. Make code reviews, branch management, and issue triaging work the way you want.
See all alternatives