
5 Use Cases: the benefits of Active-Active Redis Enterprise
What is CRDT Approach?
How Does Active-Active Redis Enterprise Work?

5 Use Cases that Highlight the Need for Active-Active Redis Enterprise

1. User Session Migration Across Data Centers
In order to achieve optimal user experience, there are times when it’s ideal to shift users to other data centers. For example, a user entering the range of a new, closer data center will experience lower latencies if they are able to establish a connection to the most proximal data center. But the ability to shift users among data centers is a challenging ask of your database if users are mid-session.
However active-active Redis Enterprise, mid-session users get routed from one data center to another in real time, seamlessly. So, all session states are preserved during the transition and both databases converge automatically to the same state with strong eventual consistency.

2. Node Failure Handling without Data Loss
As well as with user session migrations, node failure handling is seamless under active-active Redis Enterprise; so your users, along with their current session data, are automatically routed to the next nearest server. Additionally, all data is immediately consolidated, without data loss, between the two servers.

3. Immediate Data Consolidation
In many environments, especially those that employ microservices, apps have their own separate database instances. However, these instances share common datasets (user data is a typical example) which must remain consistent among the various apps. With active-active Redis Enterprise, data is resolved and consolidated immediately among the various database instances to ensure that all services are operating
with real-time data.

4. Load Distribution
Undoubtedly, the ability to distribute load across multiple servers is critical for accommodating high volumes of traffic and data streaming operations. With active-active Redis Enterprise, all database instances are available for read and write operations, optimizing resource use, maximizing throughput, and minimizing response time.

5. Geo-distributed Application Functionality
At first, it’s common for app functionality to be distributed geographically. For example, social media apps have globally distributed counters for tracking engagements such as likes, shares, or retweets. As with social media apps, apps that power auction bidding boards or gaming leaderboards must also consolidate events happening simultaneously across multiple regions and data centers. Application users need to know instantly who is in the lead.
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