Database plays an important role in data processing and storing. AWS database service is one of the most important amazon web services that provide clients with various database solutions. You may be aware of how important the role databases play in the working of the apps. AWS database services cater to all ranges of customers with different types of AWS services as per the client’s budget and their data requirement.
You can easily scale, plan, and protect big data tools with the help of data resources provided by AWS database services. The best suitable database for any project may differ as per specific requirements. This is the reason you should be aware of the various types of databases offered by AWS. This post will discuss all the AWS database services in detail.
There are two broad databases, SQL (Relational) database and NoSQL database. AWS database service is also broadly divided into these two types. Both of these types of databases are different but equally important. First, we will see all relational databases in AWS and then NoSQL databases.
Relational database (SQL)
The relational database is the most widely used database. SQL databases offer data storage in interconnected tables. In a relational database, all the data is stored in a logically structured manner that ensures data integrity. In simple language, you can use a relational database to store and utilise the information that is related to each other.
In relational databases, the table contains columns and rows for data types and records, respectively.
A relational database requires low support and less development cost. Amazon uses relational databases in CRM, ERP apps, and data warehousing.
Now we will see some famous relational database services offered by AWS.
1. Amazon RDS (Relational database service)
Amazon RDS is the most popular database service offered by AWS in the relational database category. Amazon RDS supports various database products offered by AWS and open sources. In RDS, clients can easily set up, handle, and scale up their information in the AWS database cloud, as it is less technical, and clients can operate all the things from the Amazon console with a few clicks.
One of the main advantages of Amazon RDS is that it is cost-effective compared to other database services. You can connect various apps and launch databases in RDS. Here are some use cases of Amazon RDS.
- Amazon RDS is an ideal database service for small and medium-scale eCommerce businesses. Amazon RDS can provide highly affordable and scalable database solutions to the apps of these businesses.
- You can easily set up and scale your database for your web and mobile applications.
- Amazon RDS is good for the online gaming business. It provides a good database infrastructure that can automatically scale up as per demand.
- The good feature of Amazon RDS is that it can automate various tasks like backup and restore, database set up, auto up-gradation, maintenance, and hardware provisioning.
2. Amazon Aurora
It is a database service that is entirely handled by Amazon RDS. Amazon Aurora is the database engine created for the cloud, which is very secure, scalable, and high performing.
The storage infrastructure offered by amazon aurora uses a new revolutionary cloud technology that makes it very efficient and fast. It is 5 times faster than MySQL. Also, Amazon aurora empowers its users with more features like configuration of storage framework as per their workload. Even its storage increases automatically by 10 GB with an upper cap of 64 TB, as per requirement.
One more crucial benefit of amazon aurora is that you can use your existing software, drivers, and program on amazon aurora, as it is compatible with all popular relational databases like MySQL and PostgreSQL.
Apart from that, amazon aurora offers multiple features like backup and recovery, security, monitoring, compliance, and auto restoring data even without backup.
- Amazon Aurora offers very robust database solution services, and businesses can focus on core improvement areas like building high-quality software and providing good SaaS offerings.
- Amazon Aurora offers big storage for online gaming applications.
- Amazon aurora can assist businesses in cost-cutting with the help of a large existing database.
3. Amazon Redshift
Amazon Redshift is a highly controlled and fast data warehousing service offered by AWS in the cloud. It provides various business intelligence tools to analyse your data. You can solve your complex queries within seconds with the help of huge structured data.
As per Amazon’s claim, redshift offers 10 times higher performance compared to other data warehouses. And you can scale it up to petabytes as per your requirement. One more advantage of amazon redshift is that it is cost-effective and has in-built security features that provide users with end-to-end encryption.
- Amazon redshift is highly used in business analytics, as it can solve complicated queries on various structured and semi-structured data. You can create multiple reports and dashboards for businesses with the help of different BI tools.
- You can share your data safely with internal and external users with the help of redshift.
- Redshift can be useful in predictive analytics and operational analytics with the help of a combination of huge structured and semi-structured data from the data warehouse.
Non-relational databases, also called NoSQL databases, are comparatively newer databases that do not use tables, rows, and columns. Data storage is designed for specific types of data for particular purposes like caching and logging.
NoSQL databases are used for managing large unstructured data. Here data is not stored in structured tables but in any other forms like audio files or documents. This feature makes it widely used in smartphone and computer apps.
Now we will see some widely used NoSQL database services offered by AWS.
1. AWS DynamoDB
AWS DyanmoDB is an easy-to-manage and fast NoSQL database service offered by AWS. DynamoDB can work with multiple servers located in different regions and is equipped with memory caching and inbuilt security features.
DynamoDB can handle 10 trillion requests in a day, and it comes with inbuilt backup and restore features. DynmoDB has 3 components, tables, items, and attributes.
But here, Unlike relational databases, the table is not structured with a fixed number of rows and columns. And, attributes are similar to data values in relational databases. Various identical attributes form items.
2. Amazon Neptune
It is a graph storage service offered by Amazon. You can create applications on amazon Neptune with the help of a large interconnected database. You can also store data, back up, and restore.
3. Amazon Elasticache
Amazon Elasticache provides scalable caching solutions. You can avail high performing and affordable caching services on amazon elasticache with the help of caching engines like Redis and Memcached.
Here are some benefits of elasticache apart from its simplicity,
- Elasticache retrieves data from a super speedy in-memory system. So that it reduces the response time. It does not depend on disk-based databases for data retrieval, which makes it fast.
- You can modify and scale up amazon elasticache as per the requirement of your app. Also, elasticache can make a backup recovery on its own during the failure.
4. Amazon Keyspaces
Amazon keyspace is a database service with high availability and scalability. It is compatible with open-source NoSQL databases like Apache Cassandra. Users can easily migrate their workload from Apache Cassandra to Amazon keyspace. Irrespective of any scale, customers can expect a single-digit millisecond performance on Amazon keyspaces.
Cassandra is highly preferred to store data because of its high performance and scalability. But, managing Cassandra is complicated and time-consuming. This is where amazon keyspace is useful. Amazon keyspace is serverless that enables users to form Cassandra clusters in a very short time.
All Set to Explore AWS?
So, that’s it about AWS database services. Now, you might have got the idea that relational databases like MySQL are useful when projects are small and ordinary. But when you require complex logic during the data processing in the project, then AWS database services should be used for processing both high-volume structured and semi-structured data.
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