TL;DR:
- DataStax, a DBaaS provider, is launching LunaML, a support service for its open-source unified events processing engine, Kaskada.
- LunaML offers mission-critical support with response times as low as 15 minutes and the option to escalate issues to the core engineering team.
- Two packages are available: LunaML Standard (4-hour response time) and LunaML Premium (1-hour response time), with different ticket allowances.
- DataStax acquired Kaskada to enhance its offerings in machine learning applications, including AstraDB and Astra Streaming.
- Kaskada’s capabilities address challenges related to cost, scaling, and processing large volumes of event data.
- LunaML empowers businesses to create and update features for machine learning models based on event sequences or time.
- DataStax aims to provide exceptional support and robust solutions for enterprises in real-time machine learning applications.
Main AI News:
DataStax, the leading Database-as-a-service (DBaaS) provider, is introducing a cutting-edge support service for its open-source unified events processing engine, Kaskada. This innovative solution is specifically designed to assist enterprises in building real-time machine learning applications. Known as LunaML, this service guarantees mission-critical support and offers remarkably low incident response times, with the option to escalate issues to the core Kaskada engineering team for further evaluation and troubleshooting.
LunaML presents two comprehensive packages for raising tickets: LunaML Standard and LunaML Premium. The Standard package ensures a swift 4-hour response time, while the Premium package provides an even more expedient 1-hour response time. These options cater to the diverse needs of enterprises, allowing them to select the level of support that aligns with their requirements.
In a recent blog post, DataStax highlighted that the Standard plan allows for the annual raising of 18 tickets, while the Premium plan offers the opportunity to raise up to 52 tickets in a single year. Although the pricing details for these plans have not yet been disclosed, the value they bring to businesses is undoubtedly significant.
DataStax’s acquisition of Kaskada earlier this year for an undisclosed sum reflects the company’s foresight in anticipating the surging demand for machine learning applications. By integrating Kaskada’s advanced capabilities into its existing portfolio, DataStax further bolsters its offerings, which already include the cutting-edge serverless, NoSQL database-as-a-service AstraDB and Astra фStreaming solutions.
The synergy between DataStax and Kaskada is driven by a shared vision of overcoming the challenges surrounding the cost and scalability of machine learning applications. Kaskada’s technology is uniquely engineered to process vast volumes of event data, whether it is streamed in real-time or stored in databases. Additionally, its time-based capabilities empower businesses to create and update features for machine learning models based on event sequences or the passage of time. This powerful combination opens up a realm of possibilities for enterprises seeking to leverage machine learning effectively.
With the introduction of LunaML, DataStax reaffirms its commitment to providing exceptional support and robust solutions for enterprises venturing into the realm of real-time machine learning. By leveraging this innovative service, businesses can harness the true potential of their data, unlock valuable insights, and achieve unprecedented growth in today’s competitive landscape.
Conlcusion:
The introduction of LunaML by DataStax signifies a significant advancement in the market for real-time machine learning applications. With its mission-critical support, low response times, and the ability to process large volumes of event data, LunaML empowers enterprises to harness the full potential of their data and unlock valuable insights.
This development reinforces DataStax’s commitment to providing exceptional support and robust solutions, positioning them as a key player in the evolving landscape of machine learning technologies. As businesses increasingly seek to leverage the power of real-time analytics, LunaML offers a compelling solution to address the challenges of cost, scalability, and efficient processing, paving the way for accelerated growth and innovation in the market.
