What's New at Redis? - March 2023

What's New at Redis? - March 2023

Go-Redis is Now an Official Redis Client

Beginning with Go-Redis version 9, Go-Redis is hosted under the?official Redis organization on GitHub. Go-Redis V9 includes support for the RESP-3 protocol. This aligns the Go-Redis with other officially supported Redis clients, such as?redis-py?for Python,?nredisstack?for .NET,?jedis?for Java, and?node-redis?for Node.js.?Go-Redis users will need to update their imports to reflect the version change:

// old, v
import "github.com/go-redis/redis/v8"
?
// new, v9
import "github.com/redis/go-redis/v9"8        

Redis Joins Microsoft on Artificial Intelligence Panel Discussion

Here from Sam Partee of Redis as he joins experts from Microsoft and Relevance AI to discuss Vector Similarity Search (VSS) and the capabilities it brings to use real-time search use cases.

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Looking for more details on Redis and AI uses cases? Check out this NVidia and Redis blog.

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Attend "Latency is the New Downtime" on March 21st

Learn how to protect your Redis Cache and ensure optimal user experience at all times with this technical caching webinar.

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Attend "Real Time Query and Search" Webinar on March 29th

Learn more about Redis built-in real-time search engine and about teas from tea expert and Sommelier Cara Peterson from Adagio Teas.

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Performance Focus: Speeding Up Geographic Commands

How about dropping application latency 22%? Here are the optimization techniques used to evaluate and maximize Redis GEO command performance, such as reducing wasteful computation and simplifying algorithms.

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Performance Focus: Optimizing Redis Default Compiler Flags

Compiler behavior can affect performance and code execution time. This is a deep dive into compiler performance optimization and how to squeeze out 5% faster performance by adjusting compiler flags. The GNU Compiler Collection (GCC) is?an optimizing compiler produced by the GNU Project supporting various languages, hardware architectures and operating systems. CLANG is also a GCC compatible compiler. This blog discusses optimizing both for real-time data.

Public Preview of Redis JSON geo-distributed databases on Azure

Now, developers using Azure can use a rich set of JSON commands and functions to interact with their data in up to five geo-replicated regions, ensuring that their data remains highly available and accessible to their data from anywhere. This was announced at the Azure Open-Source Day and outlined in this blog: Public Preview of JSON Support for Active Geo-Replication in Azure Cache for Redis Enterprise and Enterprise Flash tiers.

Use Cases for JSON Support for Active Geo-Replication?

Redis native JSON?capabilities already have many well-established use cases, but now expanded to a global scale on MS Azure. Below are some of the key JSON uses cases:?

  • Gaming: JSON objects can be leveraged to store game data and leaderboards, allowing for fast and efficient access to game information and player statistics across the globe?
  • Product Catalogs: Efficiently manage and search through a global dataset of products with varying SKUs and attributes ?

Get started with Redis JSON features here.

Redis Code Corner

These code examples demonstrate the complexity difference between using Hash Sets and JSON for storing data. This first code snippet is from a package.json configuration file showing simple nesting of a JSON object data.

Nested Data Structure Example

package.json

{"name": "doc-calc",

??"version": "1.0.0",

??"description": "cost calculator for json/search",

??"main": "calc.js",

??"scripts": {

????"test": "echo \"Error: no test specified\" && exit 1"

??},

??"author": "joey whelan",

??"license": "SEE LICENSE",

??"dependencies": {

????"redis": "^4.3.1"

??}

}





  • Example on the right of a typical nested JSON object.
  • Package.json file for a Nodejs application




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As more data is nested within a Hash Set, each level creates additional coding complexity.

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Nesting is much easier with the native JSON capabilities of Redis Enterprise. The nesting of object data is far easier to both create, understand and manage even as the nesting goes deeper.

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