DataStax launches Astra Streaming for continuous processing of real-time data streams

DataStax launches Astra Streaming for continuous processing of real-time data streams

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Database company DataStax Inc. is boosting its offerings with the launch of its Astra Streaming data streaming service in general availability.

Astra Streaming, built atop the open-source Apache Pulsar project, is designed to help enterprise customers get more value from their real-time data streams by analyzing that information as it’s created.

Often considered a rival to Apache Kafka, Pulsar is a publish-and-subscribe messaging platform that provides a way for software applications to communicate with one another and share data in real time. It also helps apps process information faster by eliminating the need to extract, transact and load data first, or by moving it through a data lake or data warehouse, as is normally the case with data analytics.

The platform was developed at Yahoo Inc. to combine high-performance streaming and message queuing into a single model and application program interface. The main difference between Pulsar and Kafka is that the former was designed for shared consumption, while the latter was primarily built to support single streams. As a result, DataStax argues, Pulsar is better suited for workflow applications involving multiple users.

Astra Streaming works by creating a “unified event fabric” that stretches across an enterprise’s data-in-motion, covering on premises, cloud and edge environments, DataStax said. It leverages multiple data connectors to power a real-time data ecosystem, where newly created data can flow instantly from data sources and applications to streaming analytics and machine learning systems.

DataStax said Astra Streaming has been designed to work in tandem with Astra DB, which is a NoSQL database that’s built atop of the Apache Cassandra open-source project. Astra DB is the company’s flagship product and is known for its high capacity, since it can store petabytes of data, plus its reliability, because it can withstand major outages and ensure all of the data it stores remains accessible.

DataStax said it sees Astra Streaming and Astra DB as core components of its data stack for real-time applications. By combining the two offerings, DataStax said it can offer unified data-at-rest and streaming data-in-motion capabilities, allowing users to mobilize all of their data for real-time applications, build smart apps and scale as far and as wide as they need to go.

Chris Latimer, vice president of product management at DataStax, said that’s important because many enterprises struggle to deal with fragmented and complex streaming architectures. Most data-in-motion remains siloed in legacy messaging and queuing middleware because existing tools can’t handle it, he said.

“These valuable veins of data are impossible to harvest through Kafka,” Latimer continued. “With the built-in support for Kafka, RabbitMQ and JMS, Astra Streaming makes it easy to unify all data-in-motion in a modern, multi-cloud streaming service designed for scale.”

DataStax makes a strong case for using Pulsar, and henceforth Astra Streaming, over Kafka. It cites recent research from GigaOm that shows how Pulsar has better performance and efficiency at scale compared with Kafka, especially when data is distributed geographically.

GigaOm found that Pulsar offers 35% higher performance in such cases, with costs estimated to be 81% lower over a three-year period. Latimer added that DataStax’s own research has found that organizations are becoming frustrated with both Kafka’s sprawling architecture and also the high licensing costs required to make it enterprise-ready.

“With Astra Streaming, organizations can leverage their investment in Kafka and get the benefits of superior performance, elastic scale and compelling economics… without rewriting their Kafka apps,” Latimer added.

Latimer isn’t the only one singing Astra Streaming’s praises. International Data Corp. analyst Amy Machado said that business today happens in real time, so it’s imperative for enterprises to continuously process streams of data to optimize their decision-making and actions.

“Streaming data can be a game changer for companies to make predictive business decisions and gain competitive advantages,” Machado said. “DataStax delivers a unique cloud-native architecture that can manage both streaming data-in-motion and operational data-at-rest so enterprises can get value in real time from all of their data.”

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