When it comes to managing and storing data in the cloud, there are a variety of options available to businesses. AWS (Amazon Web Services) offers several fully managed database services, allowing companies to easily store, analyze, and collect data. This blog will discuss the different types of databases and databases supported by AWS and their respective features.
Relational Databases
Relational databases store structured data and are based on the SQL language. AWS offers several relational databases, including Amazon Aurora, Amazon RDS, and Redshift. Amazon Aurora is a highly scalable, fully managed relational database engine that supports MySQL and PostgreSQL and is designed for high-performance, commercial-grade applications. Amazon RDS (Relational Database Service) is a managed database service that supports various databases, including Oracle, SQL Server, and standard MySQL databases. Amazon Redshift is a data warehouse service that allows you to analyze large amounts of data quickly and cost-effectively.
NoSQL Databases
NoSQL databases are used to store unstructured and semi-structured data, and they use non-relational data models. AWS offers NoSQL databases, including Amazon DynamoDB, DocumentDB, and Keyspaces. Amazon DynamoDB is a fully managed key-value and document database that provides single-digit millisecond performance at any scale. Amazon DocumentDB is a fully manageable document database compatible with the MongoDB API and stores data in the same document model format. Amazon Keyspaces is a managed NoSQL database service compatible with Apache Cassandra.
In Memory Databases
In-memory databases are used to store data in memory for faster access and low-latency data access. AWS offers two in-memory database services, Amazon ElastiCache, and Amazon MemoryDB. Amazon ElastiCache is a managed in-memory caching service that provides a high-performance caching layer for web and mobile applications. Amazon MemoryDB for Redis is a fully manageable, in-memory database service that offers sub-millisecond latency for high-performance, low-latency data access.
Graph Databases
Graph databases manage highly connected datasets, such as social networking and industrial telemetry data. AWS offers Amazon Neptune, a fully managed graph database service that allows you to build and run applications with highly connected datasets. Amazon Neptune provides a fast, reliable, and secure way to collect graph data.
Quantum Ledger Databases
AWS Quantum Ledger Database (QLDB) is a fully managed ledger database service that provides a cryptographically verifiable log of all data changes. QLDB allows you to track changes to data elements, making it ideal for use cases such as financial auditing, customer relationship management, and fraud detection.
How many databases are there in AWS?
If you’re looking to build a database in the cloud, AWS is a popular choice for many organizations. With AWS, you can access many purpose-built databases to suit your needs. AWS offers a selection of 15 purpose-built databases, including relational, key-value, document, in-memory, graph, time-series, and ledger databases.
With such a wide range of databases to choose from, it’s essential to select the right one for your needs. For example, a relational database might be a good choice if you need to store data in a structured way with relationships between different data points. On the other hand, a document database might be more appropriate if you’re dealing with unstructured data that can be stored flexibly.
In addition to the various database types, AWS provides managed database services that take care of many of the maintenance and management tasks associated with running a database. This can be especially helpful for organizations that need a dedicated database administrator on staff.
So, to answer the question of how many databases there are in AWS, the answer is 15 purpose-built databases. Each database type has unique strengths and features, so it’s essential to carefully evaluate your needs before selecting a database. With the right choice, you can build a robust, efficient, and scalable database that meets your needs and helps your organization succeed in the cloud.
What types of databases are supported by AWS RDS?
Amazon Web Services (AWS) offers a wide range of cloud-based services. One of them is their Relational Database Service (RDS), a managed database service that simplifies the setup and scaling of a relational database in the cloud. AWS RDS supports several popular database engines, including MySQL, MariaDB, Oracle, SQL Server, and PostgreSQL.
MySQL is an open-source relational database management system widely used for web applications, and AWS RDS supports versions 5.5, 5.6, and 5.7 of MySQL. MariaDB is a community-developed fork of MySQL that aims to be a drop-in replacement for MySQL, and AWS RDS supports version 10.0 of MariaDB.
Oracle is a widely-used commercial relational database management system, and AWS RDS supports versions 11.2, 12.1, and 12.2 of Oracle. SQL Server is another popular commercial relational database management system, and AWS RDS supports versions 2012, 2014, 2016, 2017, and 2019 of SQL Server.
PostgreSQL is a powerful and open-source relational database management system known for its robustness and extensibility. AWS RDS supports versions 9.6, 10, 11, 12, 13, and 14 of PostgreSQL, making it an ideal choice for applications that require a reliable, scalable, and flexible database engine.
In short, AWS RDS supports many popular relational database management systems, including MySQL, MariaDB, Oracle, SQL Server, and PostgreSQL. This makes it a flexible and convenient solution for organizations looking to host a relational database in the cloud. By leveraging the power of AWS RDS, businesses can focus on their applications and data without worrying about the underlying infrastructure.
In conclusion, AWS offers a big and wide range of database services for various use cases. AWS has database options for all businesses, from storing structured data in relational databases to managing unstructured data in NoSQL databases and high-performance graph databases. Whether you need to store and query log data or manage banking transactions, AWS has a database service that can meet your needs. With fully managed database services, businesses can focus on managing their data rather than managing servers and administrative tasks and take advantage of built-in security and scalability features. Additionally, AWS Database Migration Service makes migrating existing databases to AWS easy, making the transition to the cloud simple and seamless.
FAQs
What is the most used AWS database?
According to various sources, including AWS, one of the most popular and widely used AWS databases is Amazon Redshift. It is a fast, scalable, and fully-managed cloud data warehouse service that makes it easy to analyze large amounts of data using SQL and BI tools.
Amazon Redshift is known for its ability to handle large-scale analytics workloads and its speed in processing massive amounts of structured and semi-structured data. It offers columnar storage, automatic compression, and parallel processing, which enable it to deliver high performance even with petabyte-scale data sets.
Enterprises across various industries, including retail, finance, healthcare, and gaming, widely use Amazon Redshift. It is also a popular choice for data-driven startups, particularly those that deal with large volumes of data and require fast and scalable data warehousing solutions.
In summary, Amazon Redshift is one of the most popular and widely used AWS databases, known for its scalability, performance, and ability to handle large-scale analytics workloads.
What is the AWS database called?
The AWS database service is called Amazon Relational Database Service (RDS). This managed SQL database service simplifies setting up, operating, and scaling relational databases in the cloud.
Amazon RDS allows you to easily set up, and scale a relational database in the cloud. It supports popular relational database engines such as MySQL, PostgreSQL, Oracle, SQL Server, and MariaDB. Amazon RDS handles time-consuming and often tricky database administration tasks such as patching, backups, and replication, allowing you to focus on your applications and data.