How Small and Medium Businesses Can Reduce Database Storage Costs

There is an exponential increase in the amount of data that is being generated and with current rate of data creation, it will double the world’s data every two years according to Earthweb. Why is there so much data? Internet-connected devices, mobile smartphones, social media interactions, and web content are some of the sources giving rise to waves of new data being created every day. Every swipe, tap, start, or stop creates a new data point. Businesses recognize the inherent value in this data and analyze it to formulate new products, introduce services, identify market trends, improve security posture, and create workplace initiatives. Specific to small and medium businesses (SMBs), a few use cases come 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 the 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.

Another example is of vast amounts of data collected by millions of internet-connected devices. They could contain a wealth of information related to home security, manufacturing throughput, or healthcare monitoring, to name a few. Businesses are striving to have the right reporting and visualization solution to gain the insights needed to maximize operational efficiency and deliver business outcomes.

Data is deemed as useful and important for business decisions, but there are better ways to store and analyze large volumes of data that enable rapid decision making for SMBs.

Why Amazon Web Services?

Collecting large amount of data and analyzing them in a cost-effective way is challenging. AWS Cloud provides the broadest selection of storage, database, and analytics services that fit all your big data and analytics needs. It enables organizations of all sizes and industries—including SMBs—to reinvent their business with data. From data movement, storage, analytics, business intelligence, and more, AWS offers purpose-built services that are scalable and cost-effective. Smart businesses like yours are feeling the effects of economic inflation and moving data to AWS rather than expensive on-premises servers.

Why managed services?

Once businesses adopt cloud services, global reach becomes easier enabling businesses to reach millions of new customers. This results in capturing more customer data that helps drive better user experience and increased adoption of their products. However that process can result in huge volumes of data. Managing that data and analyzing it in a cost-effective way is challenging. Businesses need a solution that can do the following:

• Start small and scale to support its users whether they’re local, regional, or global
• Adopt technologies that eliminate capacity issues
• Handle software and security patching
• Monitor its infrastructure

At AWS, we suggest this approach to data management which allows SMBs to focus on building business solutions that delight their customers, while we maintain the infrastructure.

How data explosion leads to the need for serverless databases

The diagram below shows a how user interface and data access intersect. Read an example of what serverless means and how this works for inventory management. While the data architecture is comparatively easy to set up and can handle small-scale data analytics and storage without performance dissues, things get overwhelming over time. Also, the central data management team tends to become a bottleneck as data volume and usage demand increases.

Figure 1: Monolithic Architecture Diagram

Large volumes of unstructured data generated at a rapid velocity have forced data architectures to move away from a siloed approach to a distributed data architecture. Processing this large volume of data to gain business insights requires building services organized around business capabilities, also known as micro-services. These independent blocks of services can be implemented using different programming languages, databases, hardware and software environments. Micro-services combined serverless databases are critical to building global, scalable applications. Whether you have an in-house IT team or work with a tech vendor, they should be familiar with this approach.

In the following sections we will discuss in detail about AWS’s serverless database offering, the power of micro-services combined with serverless databases, and how we can help solve business problems scale.

What is Amazon DynamoDB?

DynamoDB is one of our most popular AWS data offerings to help companies manage its data in the cloud. It is a fully managed, serverless service designed to run high-performance applications at any scale. It provides following benefits:

Scalability

DynamoDB provides virtual, unlimited storage so that business can start small and continue to store infinite amount of data as their needs grow globally. Traditionally, on-premises systems couldn’t be this flexible.

Cost Effectiveness

It is considerably cheaper to store and query a large amount of NoSQL data as compared to proprietary SQL databases. If those terms are new to you, think of it this way: Structured Query Language (SQL) is a programming language data analysts knows. It is how they’ve traditionally managed and manipulated data. NoSQL is generally more flexible than SQL. Later in this blog, we will show how to lower and optimize costs further with DynamoDB.

Durability

In cases of any infrastructure failure, DynamoDB provides multiple ways to replicate or take backups of your data quickly so that businesses continue to serve their customers.

Security

Security is our top priority at AWS. DynamoDB provides access control mechanisms and encryption capabilities to help businesses address their security needs. At AWS, we use a Shared Responsibility Model.

New to digitization or looking to add more cloud capabilities to your SMB? Explore solutions by industry, benefit, use case, and more on AWS Smart Business

How customers are using DynamoDB to solve business problems that require performance and scale

DynamoDB’s ability to scale and perform with large volume of data makes it suitable for a wide variety of business use cases. If your SMB uses a CRM, location applications, or healthcare solutions, you may find it valuable.

AWS SMB customer, BeatStars, offers a music marketplace solution built using micro-services architecture and DynamoDB to connect artists, producers, and listeners. Users can browse the BeatStars marketplace for millions of artists to purchase or sell music for personal or commercial purposes. DynamoDB powers this marketplace by allowing music enthusiasts to search, store, and browse billions of rows of information related to music created by top artists. DynamoDB performance, scaling, and security has allowed BeatStars to deliver a delightful user experience to their customers.

DynamoDB is a versatile database that offers performance at scale with significant business benefits. Along with this versatility comes the complexity in managing an optimal deployment.

DynamoDB Cost Optimization Patterns

DynamoDB charges for reading, writing, and storing data in your DynamoDB tables. Most of the applications using DynamoDB are data and performance intensive, incurring cost in reading, writing, and storing data. If you work closely with an IT vendor or in-house team, they should know your application traffic patterns to save costs. In this section we will discuss cost optimization techniques.

1. Read and write cost optimization

Customers can lower cost of reading and writing data into DynamoDB if they can predict the traffic patterns of the application by reserving read and write capacity. DynamoDB reservations offer significant savings over the normal price of DynamoDB provisioned throughput capacity. However, if the traffic exceeded the reservation limits, performance is adversely affected and is subject to throttling impacting your users experience.

If your application experiences predictable traffic that gradually ramps up and down (such as seasonally), then you should use DynamoDB provisioned capacity mode to save costs. In a provisioned capacity mode, you can reserve read and write capacity you require for your application, and utilize DynamoDB auto scale features to adjust your tables provisioned capacity automatically in response to gradual traffic changes and still deliver a good user experience for their users. Learn more about DynamoDB savings by navigating to Amazon DynamoDB reservations.

If you have a new application and are unable to predict the workload behavior, you can begin using DynamoDB On-Demand capacity mode. In time, it will understand the application’s traffic pattern and switch to a reservation mode to save costs. Sometimes application traffic is unpredictable and spiky, in such circumstances use On-Demand capacity mode and application can ramp up and down quickly offering delightful user experience.

Here’s an example: In the US, the day after Thanksgiving is known as “Black Friday” which is the unofficial start of winter season shopping. That can cause a significant ramp up in your application traffic if you’re a retailer. DynamoDB provides the ability to switch between different capacity modes once every 24 hours depending on traffic. During the event, switch traffic from provisioned to On-Demand capacity mode to meet the traffic. After the event, switch back to provisioned capacity mode to save costs.

2. Storage cost optimization

Many DynamoDB applications process data at scale to make near real-time decisions. But that data is accessed less frequently over time and can be used to study trends and patterns. In such situations, SMBs want to retain data over time, but incur a lower cost to do trend analysis. In other use cases, the volume of data is so high, it may not be economical to store them to study patterns and trends. Instead, deleting the raw data and storing the summary may be more economical. DynamoDB offers features to automatically delete data to lower storage costs, as well as move the data to a lower cost storage tier to deliver significant savings.

Application data that tracks recent logins, trial subscriptions, or application metrics have limited shelf life. Amazon DynamoDB provides feature to determine when an item is no longer needed. Once the date and time of the specified timestamp has passed, DynamoDB deletes the items that have expired. This is provided at no extra cost, and the processing takes place automatically in the background and does affect read or write traffic to the table. This can save storage costs associated with DynamoDB tables.

If you are storing infrequently accessed data to study trends and patterns: such as application log, old social media posts, e-commerce order history, and past gaming achievements in DynamoDB, then use the DynamoDB Standard-Infrequent Access (DynamoDB Standard-IA) table class. This helps you reduce your DynamoDB costs for tables that store infrequently accessed data. You can learn more about it at DynamoDB table classes.

Next steps

Exponential growth in data volume has challenged SMBs to store and process information at scale to deliver business insights. DynamoDB lends itself as a data model for the serverless architecture and allows SMBs to manage large volume of data whether or not they have in-house tech talent. If you want to setup a consultation, reach out to our SMB experts. Still new to the world of cloud services? Learn more about how you can make your SMB a smart business with AWS.