
Apache Karaf
Docker
Google App Engine
Amazon S3
AWS Elastic Beanstalk
Apache ServiceMix
Cisco CloudCenter
GlusterFS
Deepnote
Apache Zeppelin
Saturn Cloud
Amazon SageMaker
Databricks Unified Analytics Platform
Azure Synapse Analytics
Google BigQuery
GeoSpock
Apache KarafBased on our record, Deepnote seems to be a lot more popular than Apache Karaf. While we know about 34 links to Deepnote, we've tracked only 1 mention of Apache Karaf. 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 Karaf with OSGi works pretty nice using annotation based dependency injection with the declarative services, removing the need to mess with those hopefully archaic XML blueprints. Too bad it's not as trendy as spring and the developers so many of the tutorials can be a bit dated and hard to find. Karaf also supports many other frameworks and programming models as well and there's even Red Hat supported... Source: over 5 years ago
Thank you for the list - I think I've come across all of these in my research! I'll try highlight the differences for each. - https://noteable.io/ - as you say, it doesn't exist anymore - https://deepnote.com - I actually mentioned this in the post but in my experience, the UX and features far behind what we've built already. I'd love to hear from anyone who's tried jupyter-ai to give us a shot and let me know... - Source: Hacker News / about 2 years ago
- https://deepnote.com -- also extensive AI integration and realtime collaboration. - Source: Hacker News / about 2 years ago
Deepnote - A new data science notebook. Jupyter is compatible with real-time collaboration and running in the cloud. The free tier includes unlimited personal projects, up to 750 hours of standard hardware, and teams with up to 3 editors. - Source: dev.to / over 2 years ago
We looked into many of these issues with Deepnote (YC S19) [https://deepnote.com/]. What we found is that these are not necessarily problems of the underlying medium (a notebook), but more of the specific implementation (Jupyter). We've seen a lot of progress in the Jupyter ecosystem, but unfortunately almost none in the areas you mentioned. - Source: Hacker News / about 3 years ago
Upload your ipynb to Deepnote and publish as an app. That simple. https://deepnote.com. - Source: Hacker News / over 3 years ago
Docker - Docker is an open platform that enables developers and system administrators to create distributed applications.
Apache Zeppelin - A web-based notebook that enables interactive data analytics.
Google App Engine - A powerful platform to build web and mobile apps that scale automatically.
Saturn Cloud - ML in the cloud. Loved by Data Scientists, Control for IT. Advance your business's ML capabilities through the entire experiment tracking lifecycle. Available on multiple clouds: AWS, Azure, GCP, and OCI.
Amazon S3 - Amazon S3 is an object storage where users can store data from their business on a safe, cloud-based platform. Amazon S3 operates in 54 availability zones within 18 graphic regions and 1 local region.
Amazon SageMaker - Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly.