Luna ML

Kaskada Open Source for ML applications with Expert Support

Experience the power of real-time ML on event data from Kaskada with peace of mind.

Benefits

Build real-time, AI-powered apps

Rich temporal event processing

Easy to use, high-performance columnar computations over event-based data. Computations like windowed aggregations, over time, for present & historical values.

Rich temporal event processing

Unified batch & real-time event-processing

Operate directly on events in real-time & observe computations on demand or materialized to a table. Execute batch analytic queries over large historical events in seconds.

Unified batch & real-time event-processing

Powerful, declarative & composable queries

Easy-to-read, type-safe, declarative queries to compute stateful aggregations, automatic joins, temporal joins, event-based windowing and pipelined operations

Powerful, declarative & composable queries

Kaskada query engine

Kaskada is a modern, open source compute engine written in Rust and built on Apache Arrow.

Kaskada query engine

Machine learning with Kaskada

Compute event-based features in historical feature computation. Prevent data leakage, or accidental computation of future events that contaminate ML models.

Machine learning with Kaskada

Develop real-time AI use-cases with peace of mind

Support engagement from DataStax to help your team develop real-time AI use cases that leverage Kaskada open source.

Develop real-time AI use-cases with peace of mind

Packages

FAQ

What is Kaskada?

Kaskada is a unified event processing engine that provides all the power of stateful stream processing in a high-level, declarative query language designed specifically for reasoning about events in bulk and in real time.

What is Luna ML?

Adding an open source component to your ML platform that supports experimentation and production environments can be complex. With Luna ML, customers can deploy Kaskada open source with the benefit of support from the Kaskada experts at DataStax.

Which Kaskada components are supported via Luna ML?

All unmodified Kaskada open source components are supported via Luna ML.

Do I need Luna ML to use Kaskada open source?

No. You don’t need Luna ML to use Kaskada open source; however, Luna ML offers support for your Kaskada deployment from the Kaskada experts at DataStax.

What is the benefit of Luna ML when using Kaskada open source?

Luna ML offers the peace of mind needed to manage your open source Kaskada deployment in production.

What are the advantages of Kaskada for real-time AI applications?

Kaskada’s declarative query language bridges the gap between batch and real time. Match model context in training and production for better performing models—without costly code rewrites.

How do I use Luna ML with Apache Cassandra and Apache Pulsar?

Depending on your requirements, you can use Cassandra and/or Pulsar as sources and sinks with Kaskada. Luna ML can help you deploy Kaskada with Cassandra and Pulsar.

Apache Cassandra can be an event store (source), feature store (sink) and prediction store (sink). Cassandra offers balanced write and query scalability, low latency, and reliability while supporting large data volumes required by ML at scale.

Pulsar can stream new data into Kaskada as a source and Kaskada can write query results by creating a materialization and writing to Pulsar as a sink in real-time.

Resources

Luna ML

Experience the power of real-time ML directly on event-data from Kaskada with the peace of mind that comes with DataStax support.

Company
Resources
Cloud Partners

DataStax, is a registered trademark of DataStax, Inc.. Apache, Apache Cassandra, Cassandra, Apache Pulsar, and Pulsar are either registered trademarks or trademarks of the Apache Software Foundation.

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