Apache Flink
Apache Spark
Spring Framework
Amazon Kinesis
Spark Mail
Grails
Apache Kafka
Apache Struts
Push Technology
Ably
Confluent
Pusher
Firebase
Apache Kafka
Lightstreamer
Socket.io
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Push Technology enables companies worldwide to build intelligent real-time applications. With Diffusion®, designed by the most creative & brightest minds in the market, build real-time, secure, high-performance applications that scale easily and satisfy today's consumer expectations under all network conditions. Along with this, build reliable data-efficient IoT, extend your data pipelines such as Kafka & enable a single view of data. Developers can integrate these features into their solution using easy-to-use and simple SDKs and REST API. Diffusion is powered by patented capabilities such as delta-streaming, comprehensive data semantics, in-memory key-value store, and more. To enquire more, visit the website.
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Based on our record, Apache Flink seems to be more popular. It has been mentiond 41 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Continuous Learning: Leverage online tutorials from the official Flink website and attend webinars for deeper insights. - Source: dev.to / 18 days ago
Apache Flink, known initially as Stratosphere, is a distributed stream processing engine initiated by a group of researchers at TU Berlin. Since its initial release in May 2011, Flink has gained immense popularity in both academia and industry. And it is currently the most well-known streaming system globally (challenge me if you think I got it wrong!). - Source: dev.to / about 1 month ago
Apache Iceberg defines a table format that separates how data is stored from how data is queried. Any engine that implements the Iceberg integration — Spark, Flink, Trino, DuckDB, Snowflake, RisingWave — can read and/or write Iceberg data directly. - Source: dev.to / about 1 month ago
The last decade saw the rise of open-source frameworks like Apache Flink, Spark Streaming, and Apache Samza. These offered more flexibility but still demanded significant engineering muscle to run effectively at scale. Companies using them often needed specialized stream processing engineers just to manage internal state, tune performance, and handle the day-to-day operational challenges. The barrier to entry... - Source: dev.to / about 1 month ago
Apache Flink: Flink is a unified streaming and batching platform developed under the Apache Foundation. It provides support for Java API and a SQL interface. Flink boasts a large ecosystem and can seamlessly integrate with various services, including Kafka, Pulsar, HDFS, Iceberg, Hudi, and other systems. - Source: dev.to / about 2 months ago
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
Ably - The definitive realtime experience platform. Built for scale.
Spring Framework - The Spring Framework provides a comprehensive programming and configuration model for modern Java-based enterprise applications - on any kind of deployment platform.
Confluent - Confluent offers a real-time data platform built around Apache Kafka.
Amazon Kinesis - Amazon Kinesis services make it easy to work with real-time streaming data in the AWS cloud.
Pusher - Pusher is a hosted API for quickly, easily and securely adding scalable realtime functionality via WebSockets to web and mobile apps.