Push Technology
Confluent
Ably
Pusher
PubNub
Apache Storm
Apache Spark
Apache Flink
Qubole
Hadoop
Google BigQuery
Apache Kafka
Amazon Kinesis
Push Technology helps companies modernize real-time applications to work under any conditions, removing the boundaries of the internet. Diffusionยฎ Intelligent Data Mesh helps you solve the connectivity, security, scalability, and data distribution challenges of your real-time solutions. Our powerful real-time SDKs and REST API make building applications simple. To enquire more, visit the website.
Push Technology enables companies worldwide to build intelligent real-time applications. With Diffusionยฎ, 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.
Push Technology Apache StormNo features have been listed yet.
Based on our record, Apache Storm seems to be more popular. It has been mentiond 11 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.
There are several frameworks available for batch processing, such as Hadoop, Apache Storm, and DataTorrent RTS. - Source: dev.to / over 3 years ago
Although this article lists a lot of targets for technical selection, there are definitely others that I haven't listed, which may be either outdated, less-used options such as Apache Storm or out of my radar from the beginning, like JAVA ecosystem. - Source: dev.to / over 3 years ago
Storm, a system for real-time and stream processing. - Source: dev.to / over 3 years ago
Google has scaled well and has helped others scale, Twitter has always been behind by years. I think the only thing they did well was Twitter Storm, now taken up by Apache Foundation. Source: over 3 years ago
Streaming: Sparks Streamings's latency is at least 500ms, since it operates on micro-batches of records, instead of processing one record at a time. Native streaming tools like Storm, Apex or Flink might be better for low-latency applications. - Source: dev.to / over 4 years ago
Confluent - Confluent offers a real-time data platform built around Apache Kafka.
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 realtime platform that just works. We power more WebSocket connections than any other pub/sub platform, serving over 2 billion devices monthly.
Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
Pusher - Pusher is a hosted API for quickly, easily and securely adding scalable realtime functionality via WebSockets to web and mobile apps.
Qubole - Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.