Google Cloud Pub/Sub
Apache Kafka
RabbitMQ
Amazon Kinesis
PieSync
Confluent
MuleSoft Anypoint Platform
Azure Logic Apps
Jupyter
Databricks
Looker
Google BigQuery
Presto DB
Rakam
Informatica
Concurrent
Google Cloud Pub/Sub JupyterNo Google Cloud Pub/Sub videos yet. You could help us improve this page by suggesting one.
Based on our record, Jupyter seems to be a lot more popular than Google Cloud Pub/Sub. While we know about 206 links to Jupyter, we've tracked only 15 mentions of Google Cloud Pub/Sub. 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.
Secondly, Go is incredibly easy to learn and in my opinion, maintain. This means that if you're a growing company and expect to onboard new teams and team members, having Go as a basis for your systems should mean that new engineers can get up to speed quickly. Below is a small sample application that can connect to Google PubSub, subscribe to a topic, send an event and then clean up. In total, its 82 lines of... - Source: dev.to / 8 months ago
Google Cloud Pub/Sub is a fully-managed, globally scalable and secure queue provided by Google Cloud for asynchronous processing messages. Cloud Pub/Sub has many of the same advantages and disadvantages as SQS due to also being cloud hosted. It has a free and paid tier. - Source: dev.to / about 1 year ago
Cloud Pub/Sub: A global messaging service for event-driven architectures. - Source: dev.to / about 1 year ago
Google Cloud Functions is a FaaS offering from Google Cloud Platform (GCP). It allows developers to run their code in response to events, such as changes in a database or the arrival of a message in a Pub/Sub topic. Like AWS Lambda, Google Cloud Functions can be used to build a variety of applications, including serverless websites, data processing pipelines, and real-time data streams. - Source: dev.to / over 1 year ago
That gets triggered when a Pub/Sub topic is fired (from the webhook function). - Source: dev.to / over 1 year ago
Interesting, I would have guessed you had used something jupyter-like: https://jupyter.org/ https://explorabl.es/all/. - Source: Hacker News / 16 days ago
JupyterLab: JupyterLab is an interactive development environment that allows you to create and share documents containing live code, equations, visualizations, and narrative text. It's particularly well-suited for data science and research-oriented projects. - Source: dev.to / about 1 month ago
Jupyter Lab web-based interactive development environment. - Source: dev.to / about 2 months ago
Choosing IDE: Selecting a suitable Integrated Development Environment (IDE) is crucial for efficient coding. Consider popular options such as PyCharm, Visual Studio Code, or Jupyter Notebook. Install your preferred IDE and ensure it's configured to work with Python. - Source: dev.to / about 1 month ago
Jupyter Notebooks is very popular among data people specially Python users. So, I tried to find a way to run the Groovy kernel inside a Jupyter Notebook, and to my surprise, I found a way, BeakerX! - Source: dev.to / 3 months ago
Apache Kafka - Apache Kafka is an open-source message broker project developed by the Apache Software Foundation written in Scala.
Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.What is Apache Spark?
RabbitMQ - RabbitMQ is an open source message broker software.
Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.
Amazon Kinesis - Amazon Kinesis services make it easy to work with real-time streaming data in the AWS cloud.
Google BigQuery - A fully managed data warehouse for large-scale data analytics.