DataStax, the lead commercial provider behind the Apache Cassandra NoSQL database, is making strides in the field of artificial intelligence (AI). On July 11-12, the company is hosting a conference in San Francisco to demonstrate how they are integrating and optimizing AI investments for success. To boost their AI capabilities, the company has recently announced Luna ML, their enterprise-supported offering of Kaskada open source, a software that helps data scientists accurately detail what AI models need to work efficiently.
Davor Bonaci, DataStax CTO and EVP, described that Kaskada Open Source is a tool that helps produce feature vectors in raw event-based data. Data can then be stored in a database—like Cassandra—and queried for finding similar vector data points. Given that Kaskada is an open source, its potential is magnified with the help of a larger community of contributors in and outside of DataStax. It has also been updated to fit the needs of large-scale users, focusing on performance, security, and reliability.
Moreover, Bonaci mentioned that Kaskada and Luna ML support MLOps—a combination of model operation and data operation—and can help identify potential bias in a dataset. As the lead company behind Cassandra and DataStax Ariaa, Luna ML is an integration of the portfolio that can benefit from more vector similarity search. Jonathan Ellis, DataStax co-founder, is overseeing community efforts to bring vector similarity search to Cassandra, aiming to keep the platform aligned with the DataStax portfolio.
To learn more, top executives can attend the conference and see how DataStax is using Luna ML and Kaskada Open Source to change the scope and usage of AI.
