What to Look for in AWS NoSQL Database

How to choose the right AWS database for your business

That depends on your business needs. Are you content with a linear, predefined approach to data management (SQL), or do you expect the state of the data you collect to change over time (NoSQL)? Fortunately, there are a few formulas you can use to make an informed decision.

RDBMS vs. NoSQL

An RDMBS is a type of database that stores data in a row-based table structure that connects related data elements. The RDMBS is characterized by the recognizable ACID properties, which are:

• Atomic – Each type of transaction must succeed, or else the whole transaction is rolled back.
• Consistent – Each transaction remains in a valid state in the database before and after completion, and it cannot leave the database in an inconsistent state.
• Isolated – Any transaction not yet committed must not interfere with another transaction and must remain isolated.
• Durable – Committed transactions remain in the database and can be recovered in case of database failure.

While these characteristics sound good on paper, there are some drawbacks to this approach to data management in terms of their lack of horizontal scaling, slow performance, fault tolerance, and availability.

This is where NoSQL comes in. The alternative to the ACID characteristics is the BASE model, which NoSQL follows:

• Basically Available – The system’s availability is guaranteed in the event of system failure
• Soft State – The state of the data can change without interfering with other applications
• Eventual Consistency – The system will eventually become consistent once it stops receiving input.

In essence, the NoSQL model relaxes some of the restrictions imposed by the ACID characteristics, trading in certain qualities like immediate consistency and total isolation in favor of a more flexible approach to data collection.

The result is the increased possibilities for greater flexibility, scale, and growth – especially when collecting data from various new and emerging sources.

Types of Amazon NoSQL Databases

With that being said, let’s see the wealth of NoSQL database options available to you. NoSQL databases are typically categorized into four different types, including:

• Key-value
• Document-based
• Column-based
• Graph-based

Each AWS NoSQL database has its own advantages. Some are better suited for websites that store large amounts of customer data and handle numerous online transactions at once, such as eCommerce stores. While others are better suited for real-time streaming services like Netflix and Spotify due to their ability to scale up and down the amount of content available quickly to users at any given time.

Below is a brief rundown of Amazon NoSQL database types.

Key-Value

Key-Value databases share the most in common with traditional SQL databases. And they are often considered the simplest type of NoSQL database. Why? Because each data element in the database is stored as a key-value pair consisting of an attribute name (or ‘key’) and a value. In this sense, the database functions as a traditional SQL database with only two columns. For these reasons, Key-Value databases are often used for consumer purposes like online shopping carts.

Document-based

Document-Based NoSQL databases store and retrieve key data as a value pair; the value part is stored as a document. What does this mean? That the value is stored in a format different from the rest of the database, such as a JSON (JavaScript Object Notation) or XML (Extendable Markup Language) format. This allows for faster indexing and querying for elements of the database while requiring less translation to use certain bits of data in different applications.

Column-based

Wide column databases use tables, rows, and columns like a traditional SQL database. The difference, though, is that the names and formats of the columns can vary from row to row in the same table. Due to this unique structure, column-based databases have high data compression rates, which helps save on disk space and speed up the query process.

Graph-based

Graph databases focus on the relationship between each piece of data. Each element is stored as a node, and the connection between each element (or node) is referred to as a link or relationship. In a graph database, a node is classified as a first-class element, that being a language entity that operates as other entities in a language. This allows a developer to ‘abstract the processing of data,’ thus having the freedom to give individual bits of data new functions during the execution of a program, such as storing them in a data structure or passing them off as arguments to other functions.