The core of AI and applications is data — various bits and bytes that are presented in an array of formats. And only when we’re able to fully sift through this data, reason with its intelligence and build on top of it with real-time results does it open the door to vast amounts of knowledge. 

Real-time insights are key to the way we live our lives today; the way we entertain ourselves; the way we listen to music; and the way we order groceries. It’s a real-time world, where everything is constantly on. Now with the influx of AI technologies and applications, the marrying of real-time and AI functionalities has never been more prevalent. 

One company well positioned to meet this new wave of technological needs is SingleStore, a database that empowers the world’s biggest brands to “transact, analyze and contextualize data in real time — without missing a millisecond,” says CEO Raj Verma. Since its inception in 2011, SingleStore has become the database of choice for companies like Hulu/Disney+, Dell, GE and more. 

The core of SingleStore’s ability to back these global organizations lies in the foundation of its database — a powerful, all-in-one tool that supports modern, real-time and generative AI applications through various data types. 

“At a super high level, we take all different kinds of data, and we elevate it to information and knowledge by bringing point-in-time data to real time,” explains SingleStore CMO Madhukar Kumar. “And when you do that, you are able to not only read, write and reason, you’re able to transact — as well as contextualize — that data.” 

Even more, this is all accomplished without sacrificing speed — something embedded in the company’s DNA and a requirement for customers using these applications. 

A few of these key data types supported by SingleStore include vectors, semantic, keyword and hybrid search, core functionalities required to make AI applications functional and responsive. 

“If you think about an exact keyword search, a lot of it is what’s been around already, “ explains Kumar. “Imagine, for example, I have a very large document, and the document could be about ‘dog’. And if I do a search and say, ‘is there a dog in this document,’ it’s going to literally look for the exact keyword. But if I now ask a question, ‘is there an animal or something about an animal in this document’, then your exact keyword doesn’t match because ‘animal’ isn’t equal to dog. That’s a classic example of a lexical search.” 

But today’s AI applications need a broader scope — a way for databases to intelligently determine an answer based on the simple context of the question. The solution? Semantic search.

“This is why semantic search has become so popular, because you want to be able to do a meaningful, or a meaning-based semantic search against your corpus of data,” Kumar says. “But the reality is, it’s not just semantic and it’s not just vectors — you also need to combine, mix and match with your other kinds of data as well.” 

It’s this combination of data types known as hybrid search that is used by so many SingleStore customers. The database can be used both on-premises and in the cloud, and built in a way to scale clusters up or down based on peaks and dips in volume. Not only does this increase cost savings, but it’s a greener, more environmentally friendly technology option. 

‍Using Real-Time Data for Good

Part of SingleStore’s core values lies in its ethical use of data, and harnessing the power of technology for good. 

“One example that’s very, very close to my heart is an organization called Thorn founded by one of our initial investors, Ashton Kutcher, “ shares Verma. “They essentially prevent sexual exploitation of children on the web.” Thorn uses real-time vector functions in SingleStore to help identify and save exploited children. 

As Verma goes on to share, there isn’t another data platform available today that empowers users to transact, analyze and contextualize data in the same platform, with millisecond response times. 

“I think the data in the world has the power to do a lot of good,” shares Verma. “And I’m personally an eternal optimist, so I do believe that data is going to be used by all of us for a lot of good.”

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