Based on our record, CircleCI should be more popular than Google Cloud Dataflow. It has been mentiond 66 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.
CI *(in our case that’s CircleCI) we run it for each *Pull Request. - Source: dev.to / 15 days ago
In this article, we are going to provide simple and detailed step-by-step instruction on how to set up Continuous Delivery for your React Native Android application by using Fabric and CircleCI 2.0. - Source: dev.to / 17 days ago
In addition, Snyk can be easily integrated with various IDEs, including Visual Studio Code and PyCharm, as well as CI pipelines, such as Jenkins, CircleCI, and Maven, and workflows. - Source: dev.to / about 1 month ago
Github Actions has many competitors in its category that allow you to run all kinds of code running on containers, such as Gitlab, Jenkins, CircleCI, etc. - Source: dev.to / about 1 month ago
It will give you a possibility to find and solve problems faster, release more stable and higher quality products. Here we will use CircleCI, but you can use whatever you need (Jenkins, Travis CI, GitLab CI). - Source: dev.to / about 1 month ago
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 1 year ago
This sub is for Apache Beam and Google Cloud Dataflow as the sidebar suggests. Source: over 1 year ago
I am pretty sure they are using pub/sub with probably a Dataflow pipeline to process all that data. Source: over 1 year 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: over 1 year 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 2 years ago
Jenkins - Jenkins is an open-source continuous integration server with 300+ plugins to support all kinds of software development
Amazon EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.
Codeship - Codeship is a fast and secure hosted Continuous Delivery platform that scales with your needs.
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
Travis CI - Focus on writing code. Let Travis CI take care of running your tests and deploying your apps.
Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.What is Apache Spark?