DataStax announced the acquisition of Kaskada. The organization wants to help customers feed artificial intelligence models with real-time data.
Developers use DataStax’s products to develop applications based on real-time data. Real-time data applications process information almost immediately after it’s generated. Think of weather forecasting, whereby data from various sensors is processed in a central system at high speeds.
Developing real-time applications with many data sources can be complex and pricey. DataStax aims to reduce costs. One of its key products is Astra DB, a cost-effective database-as-a-service for real-time data. With the acquisition of Kaskada, DataStax wants to make it easier to incorporate data from Astra DB into artificial intelligence models.
DataStax and Kaskada
Data scientists and developers use Kaskada’s software to feed artificial intelligence models with large amounts of real-time data. DataStax excels at storing such data. In that respect, the companies are two peas in a pod. “We’re thrilled to join forces”, Kaskada CEO Davor Bonaci said.
“DataStax has many customers already using real-time data, and with Kaskada as part of our services portfolio, we can give them the opportunity to use that data with real-time AI”, DataStax CEO Chet Kapoor added. “It’s an exciting time for DataStax, and we have a clear new mandate: real-time AI for everyone.”
In the short term, DataStax is making Kaskada’s core technology open source. Later this year, the organization plans to launch a cloud service for machine learning.
Focus on AI
The acquisition of Kaskada is part of a larger change for DataStax. Since its founding in 2010, the company has profiled itself as a database provider for real-time data. With the acquisition of Kaskada, the company has started profiling itself as a ‘real-time AI company‘.
The logo and corporate identity have been changed. According to DataStax, that’s part of the “evolution to becoming the real-time AI company”. We expect the acquisition of Kaskada to be just the beginning. DataStax seems set on tailoring existing products to AI.
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