Push Technology
Confluent
Ably
Pusher
PubNub
Google Cloud Dataflow
Amazon EMR
Google BigQuery
Qubole
Snowflake
Databricks
Apache Beam
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 Google Cloud DataflowNo features have been listed yet.
Based on our record, Google Cloud Dataflow seems to be more popular. It has been mentiond 14 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.
Imo if you are using the cloud and not doing anything particularly fancy the native tooling is good enough. For AWS that is DMS (for RDBMS) and Kinesis/Lamba (for streams). Google has Data Fusion and Dataflow . Azure hasData Factory if you are unfortunate enough to have to use SQL Server or Azure. Imo the vendored tools and open source tools are more useful when you need to ingest data from SaaS platforms, and... Source: over 3 years ago
This sub is for Apache Beam and Google Cloud Dataflow as the sidebar suggests. Source: almost 4 years ago
I am pretty sure they are using pub/sub with probably a Dataflow pipeline to process all that data. Source: almost 4 years ago
You can run a Dataflow job that copies the data directly from BQ into S3, though you'll have to run a job per table. This can be somewhat expensive to do. Source: almost 4 years ago
It was clear we needed something that was built specifically for our big-data SaaS requirements. Dataflow was our first idea, as the service is fully managed, highly scalable, fairly reliable and has a unified model for streaming & batch workloads. Sadly, the cost of this service was quite large. Secondly, at that moment in time, the service only accepted Java implementations, of which we had little knowledge... - Source: dev.to / about 4 years ago
Confluent - Confluent offers a real-time data platform built around Apache Kafka.
Amazon EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.
Ably - The realtime platform that just works. We power more WebSocket connections than any other pub/sub platform, serving over 2 billion devices monthly.
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
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.