How Small and Medium Businesses Can Reduce Database Storage Costs

According to Earthweb, the amount of data being generated is increasing exponentially, and at the current rate, it will double the world's data every two years. Why is there data everywhere? Every day, waves of fresh data are created from several sources, including social media interactions, site content, cell phones with internet access, and mobile gadgets. Each time you swipe, tap, begin, or stop, a new data point is created. Companies understand the intrinsic worth of this data and use analysis to develop workplace initiatives, launch new services, strengthen security posture, and develop new products. A few use cases that are unique to small and medium-sized businesses (SMBs) spring to mind.

Let’s take a common example of clickstream data analysis. Clickstream data includes small pieces of data generated continuously by users navigating through your website or mobile app. You can detect user behavior by analyzing the clicks a user makes, the amount of time they spend, where they usually begin the navigation, and how it ends. By tracking this anonymized user behavior in real time, you can understand your customers’ interests and provide updated recommendations, which improves digital experience.

Massive data sets gathered by millions of internet-connected gadgets provide another example. They might include a plethora of data about, among other things, factory throughput, home security, and healthcare monitoring. In order to obtain the insights required to optimize operational efficiency and produce business outcomes, businesses are working hard to have the best reporting and visualization solution.

Data is considered valuable and significant for company decisions; however, there are more effective ways to store and process vast amounts of data, allowing SMBs to make decisions quickly.

Why Amazon Web Services?

What makes Amazon Web Services so special?

It is difficult to gather vast amounts of data and analyze them economically. For all of your big data and analytics requirements, AWS Cloud offers the widest range of storage, database, and analytics capabilities. It makes it possible for businesses of all kinds, even SMBs, to use data to reinvent themselves. AWS provides convenient, affordable, and scalable services for a wide range of needs, including data migration, storage, analytics, business intelligence, and more. As a result of economic inflation, astute companies such as yours are shifting data from costly on-premises servers to AWS.

For what reason do you need AWS managed services?

Businesses may more easily reach millions of new clients worldwide once they use cloud services. As a result, more customer data is collected, which enhances user experience and increases product uptake. But the procedure can produce enormous amounts of data. It's difficult to manage that data and conduct cost-effective analysis of it.

Businesses need a solution that can do the following:

• To assist its users, whether local, regional, or worldwide, start small and grow.
• Adopt technology that resolves capacity concerns
• Take care of patching software and security.
• Observe its infrastructure

This data management strategy, recommended by AWS, enables SMBs to concentrate on creating customer-pleasing business solutions while we take care of the infrastructure.

How data explosion leads to the need for serverless databases

The intersection of data access and user interface is depicted in the diagram below. See an illustration of serverless computing in action for inventory control. Over time, things become overwhelming even if the data architecture is relatively simple to set up and can manage small-scale data analytics and storage without experiencing performance issues. Additionally, when demand for data usage and volume rises, the central data management team is more likely to become a bottleneck.

Monolithic Architecture Diagram

Data architectures have been pushed to transition from a siloed approach to a distributed data architecture due to the large volumes of unstructured data generated at a high pace. It is necessary to create services based on business capabilities, or micro-services, in order to process this massive amount of data and obtain business insights. Various databases, hardware, software environments, and programming languages can be used to implement these autonomous service pieces. Using serverless databases in conjunction with microservices is essential for creating scalable, worldwide applications. Your IT staff should be conversant with this method whether you engage with a tech provider or have an internal team.

The power of micro-services in conjunction with serverless databases, AWS's serverless database solution, and how we can assist in solving business problems at scale will all be covered in length in the parts that follow.

What is DynamoDB on Amazon?

One of our most well-liked AWS data solutions for helping businesses manage their data in the cloud is DynamoDB. It is a serverless, fully managed solution made to run high-performance applications at any size. It offers the following advantages:

The ability to scale

Businesses may start small and store an indefinite quantity of data as their demands develop globally thanks to DynamoDB's virtual, limitless storage. On-premises solutions were not historically able to be thus adaptable.

Economy of Cost

Large volumes of NoSQL data can be queried and stored for a lot less money when compared to proprietary SQL databases. Consider it this way if you're unfamiliar with those terms: Data analysts are familiar with the programming language Structured Query Language (SQL). It is the way they have historically handled and altered data. In general, NoSQL is more adaptable than SQL. We'll demonstrate how to use DynamoDB to further reduce and optimize costs in a later blog post.

Durability

DynamoDB offers many methods for swiftly copying or backing up your data in the event of an infrastructure breakdown, enabling companies to keep serving their clientele.

Security

For AWS, security is the first concern. Businesses may manage their security demands with DynamoDB's encryption and access control methods. AWS employs a Shared Responsibility Model.

How clients are utilizing DynamoDB to address performance- and scale-related business issues

DynamoDB is appropriate for a wide range of commercial use cases because of its scalability and performance with massive volumes of data. You might find it useful if your small business employs healthcare solutions, location applications, or CRMs.

BeatStars, an AWS SMB client, connects musicians, producers, and listeners with a music marketplace solution developed using micro-services architecture and DynamoDB. Users can peruse the BeatStars marketplace to buy or sell music for private or business use from millions of artists. This marketplace is powered by DynamoDB, which enables music lovers to search, save, and peruse billions of rows of data on music produced by leading musicians. Performance, scalability, and security of DynamoDB have enabled BeatStars to provide its clients with an enjoyable user experience.

DynamoDB is a flexible database that provides large-scale performance together with important commercial advantages. The intricacy of overseeing an ideal deployment goes hand in hand with this diversity.

Patterns of DynamoDB Cost Optimization

The reading, writing, and saving of data in your DynamoDB tables is subject to DynamoDB fees. The majority of DynamoDB applications are performance- and data-intensive, requiring money for data reading, writing, and storing. To cut expenses, if you collaborate closely with an IT vendor or internal team, they ought to be aware of your application traffic patterns.

We will talk about cost optimization strategies in this part.

1. Familiarize yourself with cost optimization

If users can forecast the application's traffic patterns and reserve read and write capacity, they can reduce the cost of reading and writing data into DynamoDB. When compared to the standard cost of DynamoDB allocated throughput capacity, DynamoDB reservations provide substantial savings. On the other hand, performance suffers and may be throttled if the traffic exceeds the reservation limitations, which could negatively effect the experience of your users.

Use DynamoDB provisioned capacity mode to reduce expenses if your application experiences predictable traffic that progressively ramps up and down (e.g., seasonally). When using DynamoDB auto scale features, you can reserve the read and write capacity that your application needs in a provided capacity mode. This allows you to automatically alter your table's provisioned capacity in response to slow variations in traffic while maintaining a high level of user experience. Go to Amazon DynamoDB reservations to find out more about DynamoDB savings.

DynamoDB On-Demand capacity option can be used if you have a fresh application and cannot forecast the demand behavior. It will eventually learn the traffic patterns of the application and transition to a reservation mode in order to reduce expenses. Use On-Demand capacity mode when application traffic is erratic and spiky to ensure a smooth user experience. The application can swiftly ramp up and down under these conditions.

As an illustration, consider this: The day following Thanksgiving is referred to as "Black Friday" in the US, marking the unofficial beginning of the holiday shopping season. As a retailer, that can result in a notable increase in application traffic. Depending on traffic, DynamoDB allows you to switch between various capacity options once every 24 hours. To accommodate the traffic during the event, move the traffic from the provided to the on-demand capacity mode. Return to provisioned capacity mode after the event to reduce expenses.

2. Optimization of storage costs

Applications using DynamoDB handle large amounts of data to enable near-real-time decision-making. However, over time, fewer accesses are made to that data, which is useful for analyzing trends and patterns. SMBs wish to keep data in these kinds of circumstances, but trend analysis is less expensive. In some use scenarios, storing the data to examine patterns and trends can not be cost-effective due to their large volume. It might be more cost-effective to save the summary and remove the raw data instead. In order to reduce storage expenses, DynamoDB has tools that allow data to be automatically deleted or moved to a cheaper storage tier, which can result in substantial savings.

Data from applications that monitor trial subscriptions, recent logins, or application metrics expire quickly. The ability to identify when an item is no longer needed is provided by Amazon DynamoDB. DynamoDB removes the expired entries after the timestamp's specified date and time have elapsed. The processing is done automatically in the background and does impact read and write traffic to the table. This is offered at no additional cost. This can reduce the storage expenses related to DynamoDB tables.

Use the DynamoDB Standard-Infrequent Access (DynamoDB Standard-IA) table class if you are keeping infrequently accessed data in DynamoDB to analyze trends and patterns. Examples of such data include application logs, old social media posts, e-commerce order histories, and historical gaming successes. This lowers your DynamoDB expenses for tables holding data that is not commonly accessed. More information about it is available at DynamoDB table classes.

Are you new to digitization or do you want to give your SMB greater cloud capabilities? Visit AWS Smart Business to explore solutions by industry, benefit, use case, and more. https://aws.amazon.com/smart-business/

SMBs are facing challenges in storing and processing data at scale to generate business insights due to the exponential expansion in data volume. Whether or not SMBs have in-house IT expertise, DynamoDB lends itself as a data model for the serverless architecture and enables them to handle massive volumes of data.