February 2017 Summaries

Kinetica has announced its integration into the Confluent Partner Program and the development of a certified Apache Kafka Connector, which allows seamless data transfer between Kafka and Kinetica's GPU-accelerated, in-memory analytics database. This integration enables joint customers to ingest real-time data streams from various sources, such as sensors and mobile apps, into Kinetica, allowing for immediate data action and real-time analysis to enhance customer experiences and operational efficiencies. The Kinetica Connector can be deployed across Confluent clusters using the Kafka Connect RESTful API, ensuring a fault-tolerant connection. Retailers, for instance, can leverage this to capture geospatial data and deliver personalized marketing offers. The collaboration between Kinetica and Confluent aims to empower businesses to harness streaming data for real-time decision-making, reflecting the growing importance of data streaming as an integral part of modern business infrastructure. Additionally, Confluent has been recognized as Microsoft's 2024 OSS on Azure Global Partner of the Year, underscoring its leadership in open-source solutions on Azure.

Confluent is hosting a Kafka Summit Hackathon on May 7th in New York City, where developers can learn how to build streaming applications with Apache Kafka. The hackathon aims to demonstrate the power of microservices combined with stream processing, using the Kafka Streams API or other Kafka clients for programming languages such as Java, C/C++, Python, and Go. Participants will have access to a vibrant ecosystem and community that provide application developers with Kafka clients for various programming languages. A panel of judges will select the most outstanding project based on creativity, features, and completeness, with prizes awarded to open-sourced code. The event is free and open to anyone, including Kafka Summit attendees.

Kafka Summit NYC, scheduled for May 8th, will feature keynote speakers and a curated agenda focused on the increasing enterprise adoption of Apache Kafka. The conference will include 24 sessions divided into three tracks—systems, streaming data pipelines, and stream processing—highlighting Kafka’s use in high-reliability scenarios across various industries. Attendees can expect to learn about Kafka’s role in demanding environments, high-performance scenarios, microservices, security, and diverse stream processing applications. The event promises insights from leading tech companies and experts, with additional activities complementing the main conference. Advance registration offers a discount, and the event aims to bring together the community to explore the latest developments in Apache Kafka and stream processing.

A survey conducted by Confluent in late 2016 on Apache Kafka community regarding their use of Kafka clients revealed Java as the most popular language used with Apache Kafka, followed by Scala and Python. Clojure was a surprising inclusion, with 13 people writing in to inform they use it with Kafka. The survey also found that 73% of respondents said they use two or more languages, with Java being the primary go-to solution for most developers. Reliability, performance, usable APIs and documentation were identified as the key factors influencing the choice of clients among several available ones. Confluent supports and maintains clients for six languages: C/C++ (librdkafka), Python, Go, C#, and JavaScript. The feedback from this survey will be used to improve the quality of Kafka clients in 2017.

The text highlights the latest updates and developments in the Apache Kafka ecosystem, including the merging of a patch designed to improve Kafka's 99% latency without user-visible changes, showcasing the detailed research involved in its JIRA documentation. The release of Apache Kafka 3.8.0 is announced, featuring new capabilities and improvements, with a suggestion to consult the release notes for comprehensive details. Additionally, the text humorously addresses the age-old "tabs or spaces" debate, proposing a Kafka-based solution using the confluent-kafka-javascript client to tally votes and display the results via a JavaScript frontend, reflecting the ongoing discussions and innovations surrounding Apache Kafka and stream processing technologies.