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AWS Greengrass VS Redis

Compare AWS Greengrass VS Redis and see what are their differences

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

AWS Greengrass logo AWS Greengrass

Local compute, messaging, data caching, and synch capabilities for connected devices

Redis logo Redis

Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.
  • AWS Greengrass Landing page
    Landing page //
    2023-03-28
  • Redis Landing page
    Landing page //
    2022-10-19

Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache and message broker. It supports data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes with radius queries and streams. Redis has built-in replication, Lua scripting, LRU eviction, transactions and different levels of on-disk persistence, and provides high availability via Redis Sentinel and automatic partitioning with Redis Cluster.

AWS Greengrass features and specs

  • Edge Computing
    AWS Greengrass allows devices to process data locally without relying on cloud resources, reducing latency and ensuring continued operation even with intermittent connectivity.
  • Seamless AWS Integration
    Seamlessly integrates with a variety of AWS services such as AWS Lambda, AWS IoT Core, and Amazon S3, allowing for enhanced functionality and simplified data exchange between edge devices and the cloud.
  • Security Features
    Offers robust security features, including data encryption for both in-transit and at-rest data, ensuring secure communication and data storage.
  • OTA Updates
    Provides over-the-air software updates, allowing developers to deploy new updates and patches to edge devices securely and efficiently.
  • Machine Learning at the Edge
    Supports ML inference capabilities, enabling machine learning models to run locally on devices, which is essential for real-time data processing and decision-making.

Possible disadvantages of AWS Greengrass

  • Complexity
    The integration of Greengrass in IoT solutions can add complexity, requiring a good understanding of both AWS services and edge computing.
  • Cost Considerations
    While processing data locally can reduce cloud costs, there may be additional expenses related to maintaining the hardware and ensuring compatibility with Greengrass, as well as costs associated with AWS usage.
  • Device Compatibility
    Not all devices may be compatible with AWS Greengrass, which may limit its use cases or require specific hardware configurations.
  • Dependency on AWS Ecosystem
    Being heavily integrated with the AWS ecosystem means that changes or outages in AWS services can potentially impact Greengrass deployments.
  • Learning Curve
    There may be a steep learning curve for developers who are new to AWS Greengrass, especially when it comes to deploying and managing complex IoT applications.

Redis features and specs

  • Performance
    Redis is an in-memory data store, which allows it to provide extremely fast read and write operations. This makes it ideal for applications requiring real-time interactions.
  • Data Structures
    Redis offers a variety of data structures, such as strings, hashes, lists, sets, and sorted sets. This flexibility helps developers manage data more efficiently in different scenarios.
  • Scalability
    Redis supports horizontal scalability with features like clustering and partitioning, allowing for easy scaling as your application grows.
  • Persistence
    Though primarily an in-memory store, Redis provides options for data persistence, such as RDB snapshots and AOF logs, enabling data durability across reboots.
  • Pub/Sub Messaging
    Redis includes a built-in publish/subscribe messaging system, which can be used to implement real-time messaging and notifications.
  • Simple API
    Redis has a simple and intuitive API, which can speed up development time and make it easier to integrate Redis into various application stacks.
  • Atomic Operations
    Redis supports atomic operations on data structures, reducing the complexity of concurrent programming and making it easier to maintain data consistency.

Possible disadvantages of Redis

  • Memory Usage
    Being an in-memory data store, Redis can become expensive in terms of memory usage, especially when working with large datasets.
  • Data Persistence Limitations
    While Redis offers data persistence, it is not as robust as traditional databases. There can be data loss in certain configurations, such as when using asynchronous persistence methods.
  • Complexity in Scaling
    Although Redis supports clustering, setting up and managing a Redis cluster can be complex and may require significant DevOps expertise.
  • Single-threaded Nature
    Redis operates on a single-threaded event loop, which can become a bottleneck for certain workloads that could benefit from multi-threading.
  • Limited Query Capabilities
    Compared to traditional relational databases, Redis offers limited querying capabilities. Complex queries and joins are not supported natively.
  • License
    As of Redis 6 and higher, the Redis modules are under the Server Side Public License (SSPL), which may be restrictive for some use cases compared to more permissive open-source licenses.

AWS Greengrass videos

Run ML Models at the Edge with AWS Greengrass ML

Redis videos

What is Redis? | Why and When to use Redis? | Tech Primers

More videos:

  • Review - Improve your Redis developer experience with RedisInsight, Redis Labs
  • Review - Redis Labs "Why NoSQL is a Safe Bet"
  • Review - Redis Enterprise Overview with Yiftach Shoolman - Redis Labs
  • Review - Redis system design | Distributed cache System design
  • Review - What is Redis and What Does It Do?
  • Review - Redis Sorted Sets Explained

Category Popularity

0-100% (relative to AWS Greengrass and Redis)
Data Dashboard
100 100%
0% 0
Databases
0 0%
100% 100
IoT Platform
100 100%
0% 0
NoSQL Databases
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare AWS Greengrass and Redis

AWS Greengrass Reviews

We have no reviews of AWS Greengrass yet.
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Redis Reviews

Redis Alternative for App Performance | Gigaspaces
Redis offers a RESTful API for accessing data stored within its in-memory technology data structures. This API provides a simple and efficient way to interact with Redis, enabling developers to leverage its capabilities seamlessly in their applications. Developers also need to manage the Redis cached data lifecycle, it’s the application responsibility to store the data &...
Are Free, Open-Source Message Queues Right For You?
A notable challenge with Redis Streams is that it doesn't natively support distributed, horizontal scaling. Also, while Redis is famous for its speed and simplicity, managing and scaling a Redis installation may be complex for some users, particularly for persistent data workloads.
Source: blog.iron.io
Redis vs. KeyDB vs. Dragonfly vs. Skytable | Hacker News
1. Redis: I'll start with Redis which I'd like to call the "original" key/value store (after memcached) because it is the oldest and most widely used of all. Being a long-time follower of Redis, I do know it's single-threaded (and uses io-threads since 6.0) and hence it achieves lesser throughput than the other stores listed above which are multi-threaded, at least to some...
Memcached vs Redis - More Different Than You Would Expect
Remember when I wrote about how Redis was using malloc to assign memory? I lied. While Redis did use malloc at some point, these days Redis actually uses jemalloc. The reason for this is that jemalloc, while having lower peak performance has lower memory fragmentation helping to solve the framented memory issues that Redis experiences.
Top 15 Kafka Alternatives Popular In 2021
Redis is a known, open-source, in-memory data structure store that offers different data structures like lists, strings, hashes, sets, bitmaps, streams, geospatial indexes, etc. It is best utilized as a cache, memory broker, and cache. It has optional durability and inbuilt replication potential. It offers a great deal of availability through Redis Sentinel and Redis Cluster.

Social recommendations and mentions

Based on our record, Redis seems to be a lot more popular than AWS Greengrass. While we know about 218 links to Redis, we've tracked only 5 mentions of AWS Greengrass. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

AWS Greengrass mentions (5)

  • Orchestrating Application Workloads in Distributed Embedded Systems: Setting up a Nomad Cluster with AWS IoT Greengrass - Part 1
    In this blog post series, we will demonstrate how to use AWS IoT Greengrass and Hashicorp Nomad to seamlessly interface with multiple interconnected devices and orchestrate service deployments on them. Greengrass will allow us to view the cluster as a single "Thing" from the cloud perspective, while Nomad will serve as the primary cluster orchestration tool. - Source: dev.to / about 2 years ago
  • AWS Summit 2022 Australia and New Zealand - Day 2, AI/ML Edition
    AWS IoT Greengrass allows one to manage their IOT Edge devices, download ML models locally, so that inference can then be also be done locally. - Source: dev.to / about 3 years ago
  • Applying DevOps Principles to Robotics
    To assist in deployment and management of workloads in your fleet, it's worth taking advantage of a fleet or device management tool such as AWS GreenGrass, Formant or Rocos. - Source: dev.to / over 3 years ago
  • Machine Learning Best Practices for Public Sector Organizations
    In some cases, such as with edge devices, inferencing needs to occur even when there is limited or no connectivity to the cloud. Mining fields are an example of this type of use case. AWS IoT Greengrass enables ML inference locally using models that are created, trained, and optimized in the cloud using Amazon SageMaker, AWS Deep Learning AMI, or AWS Deep Learning Containers, and deployed on the edge devices. - Source: dev.to / over 3 years ago
  • Looking for a good IoT overview + a simple tutorial
    Take a look at Greengrass https://aws.amazon.com/greengrass/ Enables OTA updates and fleet management. Source: about 4 years ago

Redis mentions (218)

  • Cache Invalidation: The Silent Performance Killer
    Picture this: you've just built a snappy web app, and you're feeling pretty good about it. You've added Redis to cache frequently accessed data, and your app is flying—pages load in milliseconds, users are happy, and you're a rockstar. But then, a user updates their profile, and… oops. The app still shows their old info. Or worse, a new blog post doesn't appear on the homepage. What's going on? Welcome to the... - Source: dev.to / 7 days ago
  • Feature Comparison: Reliable Queue vs. Valkey and Redis Stream
    Valkey and Redis streams are data structures that act like append-only logs with some added features. Redisson PRO, the Valkey and Redis client for Java developers, improves on this concept with its Reliable Queue feature. - Source: dev.to / 13 days ago
  • Finding Bigfoot with Async Generators + TypeScript
    Of course, these examples are just toys. A more proper use for asynchronous generators is handling things like reading files, accessing network services, and calling slow running things like AI models. So, I'm going to use an asynchronous generator to access a networked service. That service is Redis and we'll be using Node Redis and Redis Query Engine to find Bigfoot. - Source: dev.to / 27 days ago
  • Caching Isn’t Always the Answer – And Here’s Why
    Slap on some Redis, sprinkle in a few set() calls, and boom—10x faster responses. - Source: dev.to / 27 days ago
  • RisingWave Turns Four: Our Journey Beyond Democratizing Stream Processing
    Real-time serving: Many push processed data into low-latency serving layers like Redis to power applications needing instant responses (think fraud detection, live recommendations, financial dashboards). - Source: dev.to / about 1 month ago
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What are some alternatives?

When comparing AWS Greengrass and Redis, you can also consider the following products

Particle.io - Particle is an IoT platform enabling businesses to build, connect and manage their connected solutions.

MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.

AWS IoT - Easily and securely connect devices to the cloud.

ArangoDB - A distributed open-source database with a flexible data model for documents, graphs, and key-values.

Azure IoT Hub - Manage billions of IoT devices with Azure IoT Hub, a cloud platform that lets you easily connect, monitor, provision, and configure IoT devices.

Apache Cassandra - The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance.