Artificial Intelligence | News | Insights | AiThority
[bsfp-cryptocurrency style=”widget-18″ align=”marquee” columns=”6″ coins=”selected” coins-count=”6″ coins-selected=”BTC,ETH,XRP,LTC,EOS,ADA,XLM,NEO,LTC,EOS,XEM,DASH,USDT,BNB,QTUM,XVG,ONT,ZEC,STEEM” currency=”USD” title=”Cryptocurrency Widget” show_title=”0″ icon=”” scheme=”light” bs-show-desktop=”1″ bs-show-tablet=”1″ bs-show-phone=”1″ custom-css-class=”” custom-id=”” css=”.vc_custom_1523079266073{margin-bottom: 0px !important;padding-top: 0px !important;padding-bottom: 0px !important;}”]

DataStax’s Astra Streaming Goes GA With New Built-in Support for Kafka and RabbitMQ

DataStax, the real-time data company, announced the general availability (GA) of Astra Streaming, an advanced, fully-managed messaging and event streaming service built on Apache Pulsar. Now featuring built-in API-level support for Kafka, RabbitMQ and Java Message Service (JMS), Astra Streaming makes it easy for enterprises to get real-time value from all their data-in-motion.

Top Artificial Intelligence InsightsDetermining the Potential of Your AI Algorithm Starts with Measurement

“Because business happens in real time, continuously processing streams of data is imperative for enterprises to optimize decisions, actions and experiences. Streaming data can be a game changer for companies to make predictive business decisions and gain competitive advantages.”

“Many enterprises are struggling with fragmented and complex streaming architectures, with most of their data-in-motion still siloed in legacy messaging and queuing middleware like JMS and RabbitMQ,” said Chris Latimer, vice president of product management at DataStax. “These valuable veins of data are impossible to harvest through Kafka. 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.”

Astra Streaming built on Apache Pulsar: advanced streaming for real-time apps

Astra Streaming is built on Pulsar, a next-generation streaming technology built for the requirements of today’s high-scale, real-time applications. Featuring streaming, queueing and pub/sub capabilities, Pulsar is also the only streaming technology with the event semantics to address all types of data-in-motion.

More modern than earlier technologies like Kafka, Pulsar is known for its performance and efficiency at scale, especially when data is geographically distributed. Recent research from GigaOm, “A Report on the Cost Savings of Replacing Kafka with Pulsar,” found that Pulsar has a 35% higher performance and up to an 81% lower 3-year cost than Kafka.

“We’ve found that while organizations like the Kafka API, they are getting increasingly frustrated by its sprawling architecture and the high licensing costs required to make Kafka enterprise-ready. With Astra Streaming, any organization can now leverage their investment in Kafka and get the benefits of the superior performance, elastic scale and compelling economics of the Pulsar-based Astra Streaming—without rewriting their Kafka apps,” Latimer continued.

Michael Smith, founding engineer at Commonstock, said, “The Commonstock platform allows users to find and follow leading investors, learn from them and connect with friends to share verified investment insights. Similar to other social media networks like Facebook or Instagram, our business is powered by real-time data. Astra Streaming is a critical technology for our company as it powers our investment insights feed and gives users real-time mobile alerts when a new investment post or comment is shared – which is at the core of our business.”

Related Posts
1 of 40,870

AI and ML NewsWhy SMBs Shouldn’t Be Afraid of Artificial Intelligence (AI)

Key capabilities of DataStax Astra Streaming include:

  • Mobilizes all data-in-motion An enterprise’s data-in-motion encompasses all data in platforms that provide streaming, queuing and pub/sub capabilities, Astra Streaming can address all of these use cases at the scale enterprises and high growth apps need.
  • Modernizes event-driven architectures: Seamlessly leverage existing messaging/pub sub apps and turn them into streaming apps with a drop-in replacement; easily modernize Kafka applications with zero rewrites
  • Runs across an entire IT estate: multi-cloud + on prem: Supports a unified event fabric that stretches across an enterprise’s data-in-motion spread across their entire data estate: on premises, in the cloud and at the edge.
  • Powers a real-time data ecosystem: Through a wide range of connectors, Astra Streaming is connected to an enterprise’s data ecosystem, enabling real-time data to flow instantly from data sources and applications to streaming analytics and machine learning systems. It’s also integrated with Astra DB, powering its CDC capabilities.

Astra Streaming + Astra DB = the open data stack for real-time apps

Astra Streaming is a core component of DataStax’s open data stack for real-time applications. With Astra Streaming, together with the Astra DB cloud database built on the massively scalable Apache Cassandra®, DataStax offers the only stack that unifies operational data-at-rest and streaming data-in-motion. With DataStax, enterprises can mobilize all enterprise data for real-time applications, build smarter applications faster, and scale without limits on any cloud.

Amy Machado, IDC Research Director, Streaming Data Pipeline, commented: “Because business happens in real time, continuously processing streams of data is imperative for enterprises to optimize decisions, actions and experiences. Streaming data can be a game changer for companies to make predictive business decisions and gain competitive advantages.”

“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. DataStax Astra Streaming is powered by Apache Pulsar and has built-in support for Kafka, RabbitMQ and JMS, offering enterprises a wide set of capabilities within its single, unified platform,” Machado continued.

Latest Aithority Insights: Why Contextual Targeting Deserves Another Look with Artificial Intelligence (AI)

[To share your insights with us, please write to sghosh@martechseries.com]

Comments are closed.