Redis Sentinel vs Cluster – Which is Better? (Pros and Cons)

Redis Sentinel vs Cluster – Which is Better?.  In this article we will discuss the differences between Redis Sentinel vs Cluster with their pros and cons.

Redis Sentinel provides high availability for Redis. In practical terms, using Sentinel, you can create a Redis deployment that resists certain kinds of failures without human intervention.

Redis Cluster provides a way to run a Redis installation where data is automatically sharded across multiple Redis nodes. Redis Cluster also provides some degree of availability during partitions. In practical terms, the ability to continue the operations when some nodes fail or cannot communicate.

what is Redis message broker

Redis Sentinel

If you have a single Redis instance and that instance goes down for some reason, you are doomed because your application depends on Redis to store data, and if your data source is down, your application is out of luck. To resolve this issue, you could add slaves to replicate your master and then just read it from the slaves until your master comes up again. Though this is one way to do it, there is a more reliable way to do that simply; it is Redis Sentinel.

Redis Sentinel is a system designed to help manage Redis instances. The primary purpose of using sentinel is to provide a high availability system by monitoring, notifying, and providing instance failover. In addition, the sentinel performs the following three tasks:

 

  • Monitoring: This is basically when sentinel checks if the master and slave instances are working as expected.
  • Notification: This is when the sentinel notifies other programs or other system administrators via an API when there is something wrong with the monitoring instances.
  • Automatic Failover: On a master failure, the sentinel promotes one of the slaves to become the new master and then makes the other additional slaves use the new master. 
Redis Sentinel Master Slave

It is worth mentioning that sentinel acts as the source of authority for clients. For example, clients connect to sentinel to ask for the address of the current Redis master.

There are a few things to consider when working with sentinels. First, it is recommended to have at least three Sentinel instances run on servers that fail independently. Though it is unnecessary to run the Sentinel nodes on separate servers, they can be run as parallel processes on the Redis nodes themselves. Second, Redis’s client must have Sentinel support. For example, if you use a Java application client or a Python application client, you need to make sure that this client supports working with sentinels.

Another point to know about the Redis Sentinel is that it is nothing more than a specific execution mode of the Redis server itself. Instead, Sentinel has a set of APIs that provide information on the running instances. So, for example, you can run a specific command like SENTINEL masters would show a list of monitored masters and their states.

Redis Cluster

A stable version of Redis Cluster was introduced in Redis version three. Redis Cluster is a data sharding solution with automatic management, failover, and replication.

Data sharding is a method to break up a big database (DB) into smaller parts. It is the process of breaking up a database across multiple machines to enhance the manageability, availability, performance, and load balancing of an application. The reason for data sharding is that after a certain scale point, it is cheaper and more attainable to scale horizontally by adding more machines than to grow it vertically by adding beefier servers.

Generally, the cluster mode provides similar high availability to Sentinel mode but the sharding allows more data to be stored in the cluster. As a result, cluster improves the scalability of your application as data continues to grow.

Redis Cluster Master Slave

Redis Sentinel vs Redis Cluster

Redis Sentinel is a good option for a smaller implementation with high availability concerns. On the other hand, Redis Cluster is a clustering solution that handles the scanning for larger implementations. Redis cluster splits your data across several, and it provides failover, automatic management, and replication in one package. This type of solution is excellent for a high availability system when you also have to consider the speed of accessing your data.

Architecture

Redis Cluster does not have a central architecture; it automatically splits data among different nodes. Also, you need a minimum of three master nodes and three slave nodes(six nodes). In the case of Redis Sentinel, it is possible to build a fully functional Sentinel deployment using only three nodes.

Availability

Redis Sentinel has very high availability; this is helpful because, without human intervention, it allows building a Redis Sentinel deployment that can survive multiple failures. Also, it can survive the failure of all slave instances if even one master instance is available. On the flip side, Redis Cluster does not have high availability. In case of a significant failure, for example, if most of the masters are unavailable, the cluster stops.

Scalability

Talking about scalability, it is straightforward in Redis Cluster. You can easily add or remove the nodes in the cluster. Redis Cluster allows you to add or remove nodes dynamically. Also, it supports up to a thousand nodes in the system. Contrarily, Redis Sentinel is not scalable. The writes are directed to the master; therefore, it cannot solve the read-write separation problem.

Data Sharding

Data sharding is a specific type of data partitioning. Data sharding is a specific type of data partitioning. Sharding is the process of splitting data into smaller chunks or shards. Each shard or chunk can be on a different machine, or they can also be on the same machine. Without sharding, all the data will remain in one machine. With the database sharding, you can potentially split the data into multiple machines.

It is just an optimization technique that lets you split your data into smaller parts. So that now instead of having large data, you have smaller individual ones, and each of those can have the same kind of hardware set up; therefore, you get better performance and more data storage.

Redis Sentinel is not a good option when it comes to data sharding. It does not have this ability, due to which the utilization of master and slave becomes imbalanced. Contrastingly, when clients have network access to all nodes, Redis Cluster shards the data among multiple masters.

Replication

Both Redis Cluster and Redis Sentinel allow replication of the data, but both have their issues. Redis Cluster’s replication structure does not allow multiple layers, you can only replicate the master node to the slave node. At the same time, Redis Sentinel allows replication to multiple slave nodes from a master node. However, both Redis Cluster and Redis Sentinel asynchronously replicate the data, compromising consistency.

Redis Sentinel vs Redis Cluster Final Thoughts

Both provide high availability for your system. When speed is not your primary concern, you should use sentinel, making it an excellent option for smaller implementations with high availability concerns. On the other hand, Redis Cluster provides high availability plus a clustering solution. It is a perfect choice to ensure high availability while keeping fast access speed in consideration to access your data.

If you need an automatic failover solution without going to a complete cluster solution, use Sentinel. To get a complete cluster solution that splits your database between multiple nodes, then go for clustering.

Avatar for Emad Bin Abid
Emad Bin Abid

I'm a software engineer who has a bright vision and a strong interest in designing and engineering software solutions. I readily understand that in today's agile world the development process has to be rapid, reusable, and scalable; hence it is extremely important to develop solutions that are well-designed and embody a well-thought-of architecture as the baseline. Apart from designing and developing business solutions, I'm a content writer who loves to document technical learnings and experiences so that peers in the same industry can also benefit from them.

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