Saturn Cloud
Amazon SageMaker
Databricks Unified Analytics Platform
Apache Zeppelin
Azure Synapse Analytics
Deepnote
Google BigQuery
GeoSpock
Entity Framework
Sequelize
MyBATIS
Hibernate
Quick Objects
Mikro orm
Dapper
Doctrine
Saturn Cloud is an award-winning ML platform with 75,000+ users, including NVIDIA, CFA Institute, Snowflake, Flatiron School, Nestle, and more. It is an all-in-one solution for data science & ML development, deployment, and data pipelines in the cloud. Users can spin up a notebook with 4TB of RAM, add a GPU, connect to a distributed cluster of workers, build large language models, and more in a completely hosted environment.
Data scientists and analysts work best using the tools they want to use. You can use your preferred languages, IDEs, and machine-learning libraries in Saturn Cloud. We offer full Git integration, shared custom images, and secure credential storage, making scaling and building your team in the cloud easy. We support the entire machine learning lifecycle from experimentation to production with features like jobs and deployments. These features and built-in tools are easily shareable within teams, so time is saved and work is reproducible.
Saturn Cloud Entity Frameworkfast, easy to create container, clear bill
I have used many alternative platform but nothing comes close to this
Smooth and bug free experience. There are ready data science images with pre loaded packages for most common scenarios, making you focus on the project/problem and leave the infrastructure part to Saturn Cloud.
Based on our record, Entity Framework should be more popular than Saturn Cloud. It has been mentiond 15 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.
After the MLOps tooling evaluation, our focus shifted to data engineering. Some teams in the company were already using tools like Dask and xarray to manage and process their datasets. The architect was determined to build a data lake for the organization. The vision was to make xarray datasets accessible via Intake, using a Dask-capable computing platform. For the compute platform, we explored services like... - Source: dev.to / over 1 year ago
Not 100% sure of your intention, but if you work with python, and you're familiar with (or can spend the time learning) dask, and willing to pay, you can consider coiled.io or saturncloud.io that offer managed dask that you can scale and use GPUs etc (again, not sure if applicable to your use case). Source: over 3 years ago
SaturnCloud - Data science cloud environment, that allows to run Jupyter notebooks and Dask clusters. 30 hours free computation and 3 hours of Dask per month. - Source: dev.to / over 3 years ago
I think your site looks good and I have used the type of service you offer, but there are 2 potential problems. As SheepherderPatient51 said,Google already offers all of this for free (and so does https://kaggle.com and https://www.paperspace.com ). There are also other sites just like yours such as https://deepnote.com,https://saturncloud.io, and https://lambdalabs.com . Source: over 3 years ago
* How does it differ from other GPU cloud providers that offer ready to use Jupyter notebooks? (E.g. https://support.genesiscloud.com/support/solutions/articles/47001170102-running-jupyter-notebook-or-jupyterlab-on-your-instance or https://saturncloud.io/). - Source: Hacker News / over 4 years ago
For the simplicity we will use MSSQLProvider to fetch the data from the database. This class has basic functionality, if you want to create complex database queries, for example JOIN, you'd better use something like Entity Framework. - Source: dev.to / about 2 years ago
I only wanted to give a simple preview of what can be done with Entity Framework, but if this is something that interests you and you want to go further in-depth with all the possibilities, I recommend checking out the official docs where you can also find a great tutorial which will guide you through building your very own .NET Core web application. - Source: dev.to / about 3 years ago
Entity Framework documentation hub - Entity Framework is a modern object-relation mapper that lets you build a clean, portable, and high-level data access layer with .NET (C#) across a variety of databases, including SQL Database (on-premises and Azure), SQLite, MySQL, PostgreSQL, and Azure Cosmos DB. It supports LINQ queries, change tracking, updates, and schema migrations. Source: about 3 years ago
You can create the DAL using your existing code or start using a Object Relational Mapper like Entity Framework which will do a lot of the work for you, check this out here: https://learn.microsoft.com/en-us/ef/ also check out LINQ. Source: over 3 years ago
And, possibly (not strictly speaking necessary but very useful) Entity framework as a backend part of it. Source: over 3 years ago
Amazon SageMaker - Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly.
Sequelize - Provides access to a MySQL database by mapping database entries to objects and vice-versa.
Databricks Unified Analytics Platform - One platform for accelerating data-driven innovation across data engineering, data science & business analytics
MyBATIS - MyBatis is a top-rated SQL-based data mapping solution used by Programmers, Software Engineers, and Database Architects for developing object-oriented software applications.
Apache Zeppelin - A web-based notebook that enables interactive data analytics.
Hibernate - Hibernate an open source Java persistence framework project.