Apache Spark
Apache Flink
Hadoop
Apache Storm
Apache Kafka
Apache Hive
Google Cloud Dataflow
Apache Airflow
Push Technology
Ably
Confluent
Pusher
Firebase
Apache Kafka
Lightstreamer
Socket.io
Push Technology helps companies modernize real-time applications to work under any conditions, removing the boundaries of the internet. Diffusion® 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 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 Spark seems to be more popular. It has been mentiond 70 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.
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
Apache Spark powers large-scale data analytics and machine learning, but as workloads grow exponentially, traditional static resource allocation leads to 30–50% resource waste due to idle Executors and suboptimal instance selection. - Source: dev.to / about 2 months ago
One of the key attributes of Apache License 2.0 is its flexible nature. Permitting use in both proprietary and open source environments, it has become the go-to choice for innovative projects ranging from the Apache HTTP Server to large-scale initiatives like Apache Spark and Hadoop. This flexibility is not solely legal; it is also philosophical. The license is designed to encourage transparency and maintain a... - Source: dev.to / 3 months ago
[1] S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach. Pearson, 2020. [2] F. Chollet, Deep Learning with Python. Manning Publications, 2018. [3] C. C. Aggarwal, Data Mining: The Textbook. Springer, 2015. [4] J. Dean and S. Ghemawat, "MapReduce: Simplified Data Processing on Large Clusters," Communications of the ACM, vol. 51, no. 1, pp. 107-113, 2008. [5] Apache Software Foundation, "Apache... - Source: dev.to / 3 months ago
If you're designing an event-based pipeline, you can use a data streaming tool like Kafka to process data as it's collected by the pipeline. For a setup that already has data stored, you can use tools like Apache Spark to batch process and clean it before moving ahead with the pipeline. - Source: dev.to / 4 months ago
Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
Ably - The definitive realtime experience platform. Built for scale.
Hadoop - Open-source software for reliable, scalable, distributed computing
Confluent - Confluent offers a real-time data platform built around Apache Kafka.
Apache Storm - Apache Storm is a free and open source distributed realtime computation system.
Pusher - Pusher is a hosted API for quickly, easily and securely adding scalable realtime functionality via WebSockets to web and mobile apps.