Cloud databases, like most business-to-business technology, act as the behind-the-scenes mechanics of a stage production, seamlessly orchestrating the flow of application data for organizations and consumers who are unaware of their impact on daily digital experiences. Online and in-person shopping, gaming, video streaming, restaurant reservations and travel – the list goes on – cloud databases power mission-critical applications that we all rely on. That’s why we celebrate National Cloud Database Day annually on June 1. This official day was created to raise awareness of the value of cloud databases and how they are the backbone of modern enterprises and digital experiences. To celebrate this year, we’re examining how developers can fuel successful AI adoption with cloud databases in the generative AI (GenAI) era.

As GenAI becomes more mainstream with the help of ChatGPT and other large language models (LLMs), its potential impact is captivating enterprises and consumers. Given the technology’s productivity and efficiency benefits, from prototyping and testing new ideas quickly to making developers more efficient, enterprises across industries are implementing GenAI in IT modernization projects like documentation chatbots and coding assistants. In fact, research from Couchbase found that 73% of enterprises are increasing investment in AI tools to help developers work more effectively and create new applications faster.

The signs are clear. Enterprises have entered the age of AI. Nearly every organization we surveyed listed using GenAI in their operations as a goal this year. When used effectively, this technology can play a vital role in helping enterprises address business challenges, including meeting continually increasing demands for developer productivity and keeping pace with end-user expectations. 

AI needs a multipurpose cloud database

To be successful with AI, enterprises must ensure their infrastructure and data management strategies can meet the demands of GenAI. Without fast access to accurate, tightly managed data, there’s a risk of GenAI leading developers’ applications astray. It’s also important for enterprises to have confidence that they are not putting proprietary or sensitive data at risk because they don’t have the right controls in place or driving up operational costs because AI is expensive and their guardrails aren’t set up.

Furthermore, 71% of IT departments are under growing pressure to do more with less. Enterprises need to increase developer productivity by 33% year-on-year simply to remain competitive. That’s why it’s important for developers to have access to multipurpose cloud databases that simplify how they develop, deploy, and run AI-powered adaptive applications from a single platform. This includes cloud databases that enable developers to use natural language to quickly and easily generate code, sample datasets, and unit tests, that also have the familiarity of SQL as the query language to help developers get up to speed quickly.

Choosing the right multipurpose cloud database can help enterprises empower their developers to meet GenAI goals. However, there are barriers. 66% of enterprises want to update databases to better support in-house GenAI applications but believe that they have to buy multiple databases to acquire all the necessary capabilities. Contrary to this belief, enterprises do not need to invest in multiple databases to build AI applications. We argue that using a multipurpose database that simplifies and eliminates complexity from data architecture will produce better quality code and more trustworthy responses from LLMs. GenAI is forcing enterprises to complete their data modernization projects with a new mindset focused on how to create trustworthy interactions with AI. This helps them realize that AI hates complexity. 

There are modern multipurpose cloud databases like Couchbase Capellaâ„¢ that make AI experimentation easy for developers by including vector search as a feature rather than installing another database. These multipurpose databases offer multiple data access patterns to create feature-rich applications without the added work of using purpose-built databases. Developers will recognize that the flexibility offered by the JSON format is ideal for building AI interactions because it can store prompt instructions and variables and extend AI conversations by storing LLM responses. Developers will also appreciate that incorporating real-time analytic metrics as prompt variables will help the relevance of the conversation. And finally, they will see that a majority of contextual information can be provided from mobile devices. This context can include location, situation, news, and activity information that originates and is consumed on devices in the hands of users. Of course, these kinds of capabilities must address latency issues and scale as needed. Multipurpose cloud databases help businesses meet their data management and context requirements without needlessly increasing AI infrastructure demands.

The future is adaptive

Cloud databases can provide the distributed, high-speed analytics and feature processing that AI requires so organizations are well positioned to afford or offset the costs of GenAI. This will encourage developers to think beyond chatbots and content generators and invent a new generation of AI-powered adaptive applications that can adjust behaviors and features in real time based on various factors, including user preferences, environmental conditions, data inputs, or changing circumstances. This will provide a hyper-personalized and responsive end-user experience by tailoring app functionality to the specific needs and current context of the user on the fly.

We are still at the early days of GenAI, and at Couchbase, we are committed to exploring the full potential of this technology and its impact on cloud databases. As we celebrate National Cloud Database Day, let’s take time to appreciate the possibilities of where AI and the right data architecture will take us.

Additional resources:

Author

Posted by Jeff Morris, VP Product Marketing

Jeff Morris is VP of Product and Solutions Marketing at Couchbase. He's spent over three decades marketing software development tools, databases, analytic tools, cloud services, and other open source products. He'd be the first to tell you that anyone looking for a fast, flexible, familiar, and affordable cloud-to-edge database-as-a-service can stop looking after they check out Couchbase.

Leave a reply