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Cloud data platforms are increasingly becoming a part of the modern data stack, decreasing data silos and making all their application data available to the entire organization from a single system. While this has provided significant commercial benefit, it has also resulted in the unintended effect of creating “knowledge silos” since application logic, defined as code in source applications, is left behind. Data science and the next generation of data applications represent relationships that are too complicated for SQL to manage, necessitating a different application stack, programming model, and procedural language.
Relational knowledge graph, a new generation of database systems, is trying to incorporate complicated business logic and machine learning into the database itself. By merging database systems with relational knowledge graphs, tech startup RelationalAI is reinventing data app development by making it more straightforward for domain experts and developers to collaborate and construct intelligible, executable business logic.
Using underlying relational technology, the RelationalAI invention integrates application logic and relationships. It’s a technology that lets everyone access, interpret, and alter intelligent data, bringing business expertise much closer to corporate data. Google and LinkedIn were among the first to use knowledge graphs to improve search results and better comprehend people’s connections. RelationalAI is bringing this sort of power to every business, allowing them to innovate and gain a competitive advantage.
By allowing data apps to be developed declaratively in the database, RelationalAI completes the contemporary data stack. This enables data apps to access information for sophisticated tasks such as reasoning and graph analytics, mathematical optimization, and machine learning, all while remaining within the confines of a fully functional, modern data stack. The RelationalAI system is available as a fully hosted cloud service with consumption-based pricing and self-service tooling to make knowledge graph-based applications simple to create.
The Berkeley-based startup has raised $75M in a Series B funding round, led by Tiger Global, with participation from existing investors, Menlo Ventures, Madrona Venture Group, and Addition. With this round, the company’s total raise comes down to $122M.
RelationalAI will use these funds to speed up product development and go-to-market efforts for their relational knowledge graph technology.
Consultant Intern: Currently in her third year of B.Tech from Indian Institute of Technology(IIT), Goa. She is an ML enthusiast and has a keen interest in Data Science. She is a very good learner and tries to be well versed with the latest developments in Artificial Intelligence.