What Is Memory DB? Creating And Configuring MemoryDB Clusters

A Memory DB known as a “Memory Database” is a type of open-source data storage that is designed in such a way that it can perform the read and write operations very quickly. It is made for applications that need very high-speed data speed and low latency response. This MemoryDB is Durable in nature and was built for modern applications with microservices architectures.

A MemoryDB Cluster is made up of multiple nodes that are interconnected and distributed such that they share and manage the data very quickly. The use of the MemoryDB cluster has eliminated the need to separate and manage a cache and durable database.

What is MemoryDB?

It is a high-speed in-memory database service that delivers ultra-fast performance and strong consistency. MemoryDB is compatible with Redis which is a popular open source data store. It enables the user to quickly build applications by the use of flexible and friendly Redis data structures, APIs, and commands that are in use today. MemoryDB is also used to store data across multiple Availability Zones (AZs) and help its users overcome fast failover, database recovery, and node restarts.

A MemoryDB cluster is a group of network servers that work together to store and manage data in memory. Every server contributes some of its RAM to store a part of the overall database. This allows the database to store beyond the memory capacity of a single server. Clusters are used because they provide surplus and high-availability database storage using replication. The Nodes in a cluster are connected to each other with the help of high-speed networks to reduce latency whenever the servers communicate and replicate data.

Features of MemoryDB

The following are the features of the MemoryDB:

• It uses a single and primary database to work for the clusters and to provide consistency to the user application.
• A MemoryDB delivers ultra-fast performance and strong consistency to the database and helps the user to quickly build applications.
• It uses high-speed RAM or flash memory like SSDs rather than the slower hard disks to store the data in the database which is faster to read and write.
• It acts as a Load balancer by Spreading the database requests to multiple servers and distributing the work evenly so that no server is overloaded.
• It uses replicas that maintain multiple copies of the database on different servers so if one server fails, the database is still available from the other replicas.
• It is able to handle the increased data in the database and traffic in the server by easily adding more servers.
• It accesses the data in memory caches to avoid slower disk access and for the same, it uses popular caches like Redis and Memcached to store data in RAM for microsecond access.
• It is usually that memory is more expensive than disk but the performance is much better. The Declination of memory prices can help improve cost-effectiveness.

Creating and Configuring MemoryDB Clusters

Step 1: Go to AWS management console and search for the Amazon MemoryDB for Redis.

Step 2 : On the left side of your screen, click on the Clusters to create a new cluster or view your clusters. After clicking on the clusters, click on the create clusters to add a new cluster.

Step 3: After clicking on create new cluster, fill all mandatory details asked by AWS management console to add a new cluster. Fill out the necessary details using the instruction below or you can take the help from the Aws management console center.

Property	Description
Cluster Info	Select the Create new cluster option. Give the name to your cluster and Description(optional) about the cluster.
Subnet Group	Select create new subnet group and Fill out the Name, Description, and VPC ID of the cluster. The VPC ID can be new or existing according to AWS Console to run your cluster.
Others	In the other, fill out the necessary details like Port 6379 (which can run in all the available zones), Parameter group (select the default.memorydb-redis6),node (default), Number of shards and replicas per shards (according to your cluster usage).
Advanced Setting	You can manage the security according to you or can use the Encryption key (default key) to manage it by AWS management console.
Inbound Rules & Snapshot	Select the Port 6379 (default)under the inbound rules and Enable automatic snapshots. Enter the snapshot retention period according to you and select the snapshot window as no preference or specify the snapshot window accordingly.
Maintenance Window	Select the No preference for default setting or Select your own preference Maintenance Window and fill out the mandatory setting according to you.

Step 4: Click on the create cluster. It may take 15-20 minutes to create your cluster and get it ready to configure so you need to wait for your cluster to complete and configure it.

Step 5: Till your cluster gets ready to use, Go to EC2 Services and Click on the launch instances to create a new instance. Later, configure this instance with your cluster and console to work into your MemoryDB.

Step 6: Select the AMI (Amazon Machine Image) you want according to the purpose and use of your instance in the cluster. However, for best ultra performance and free cost, use the Amazon kernel 5.10 64-bit (*86). Then Review and launch it.

Step 7: Wait for your instance to get ready and check out the position of your cluster. Keep refreshing it to check the position of the instance and the cluster. Once both are done, Go to the cluster and copy the Endpoint of your cluster.

Step 8: Now Connect your EC2 Instance created by you and wait for the console to open.

Step 9: After establishing the connection to your instance and configuring your cluster and instance, follow the following command to access your cluster and read, write your MemoryDB Cluster. Now for that, Install the Redis CLI. Connect to your EC2 instance via SSH using the private key associated with your instance.

wget http://download.redis.io/redis-stable.tar.gz

Step 10: Run the following command to initialize the Redis CLI to the environment and your Cluster.

tar xvzf redis-stable.tar.gz

cd redis-stable

make distclean

make redis-cli BUILD_TLS=yes

Sudo install -m 755 src/redis-cli /usr/local/bin/

Step 11: Connect to your MemoryDB Cluster From EC2 by: Then you will be connected to your cluster and access you MemoryDB.

src/redis/-cli -c -h #copy the endpoint copied from your cluster page and run the code

Advantages of MemoryDB Cluster

1. It provides ultra fast performance because of its nature of in-memory storage.
2. It is highly flexible because it can increase or decrease the cluster size by adding or removing nodes on the fly.
3. It supports automatic data replication and failover for high availability.
4. This is a fully managed service, so user don’t have to worry about maintenance tasks.
5. Their is robust security features available-in such as encryption and access control.
6. It also supports the advanced Redis data types and commands so is said to be user-friendly.
7. We can integrates with it seamlessly with other AWS services.
8. It is also cost-effective because it works on the principle of “pay-as-you-go” pricing model.

Disadvantages of MemoryDB Cluster

1. It could be costly if we are setting up and running a MemoryDB cluster for a large deployments or high-availability setups.
2. It is complex to manage because it is difficult to manage a multi-node MemoryDB cluster because it shows issues while configuration, scaling, monitoring, and troubleshooting for optimal performance and availability.
3. It has the Limited Availability Zones so MemoryDB clusters may have restrictions and also they can span the potentially impacting fault tolerance.
4. It has limited customization services so as a managed service, MemoryDB may not support advanced Redis configurations or extensions, limiting flexibility into some cases.

Conclusion

The use of MemoryDB clusters gives us very fast and in-memory databases that work nicely with other AWS services. But there are some things to think about. They can get costly according to our application size, especially for big setups or high availability. It difficult for us to manage clusters with multiple servers and we need to have knowledge about the technical setup, scaling, monitoring, and troubleshooting. At last, they might be limited to only a few AWS locations, which could impact relativity. However, we also can’t ignore that MemoryDB has awesome speed and convenience are worth these potential drawbacks. We can integrates with it seamlessly with other AWS services and we don’t have to worry about maintenance tasks. MemoryDB cluster is a group of network servers that work together and help its user to overcome fast failover, database recovery, and node restarts. So we can conclude that it saves, both the time and effort of the user.

Memory DB – FAQ’s

What do you mean by MemoryDB?

Memory Database is a type of open source data storage that is designed in such a way that it can perform the read and write operations very quickly.

Why is there a need of the MemoryDB Clusters?

MemoryDB Clusters allows the database to store beyond the memory capacity of a single server. Clusters are used because they provide surplus and high availability database storage using replication.

How does the MemoryDB Clusters work?

The Nodes in a cluster are connected to each other with the help of the high speed networks to reduce latency whenever the servers communicates and replicate data.

Explain any two features of MemoryDB Clusters.

It uses a single and primary database to work for the clusters and to provide consistency to the user application.

What are the limitations of the MemoryDB Clusters?

They can get costly according to our application size, especially for big setups or high availability. It difficult for us to manage clusters with multiple servers and we need knowledge about the technical setup.