Saturn Cloud
Amazon SageMaker
Deepnote
Databricks Unified Analytics Platform
Apache Zeppelin
Azure Synapse Analytics
GeoSpock
Google BigQuery
ArangoDB
Redis
MongoDB
OrientDB
neo4j
Apache Cassandra
Azure Cosmos DB
CouchBase
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 ArangoDBSmooth 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.
True story, way better than just sweating Colab. The best and cheapest compute services there is.
I have started using this to run the computations which generally require like 64+GB of RAM, and the procedure to setup the enviroment is also nice. Got all the R packages running smoothly.
Saturn Cloud might be a bit more popular than ArangoDB. We know about 7 links to it since March 2021 and only 6 links to ArangoDB. 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 / 4 months 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: about 2 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 2 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 2 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 / about 3 years ago
If you like the document db idea there are a lot of choices, especially https://arangodb.com/ which I think gets little attention because people who use it see it as a secret weapon. Too bad about the license though. Also https://couchdb.apache.org/ and https://developer.marklogic.com/. - Source: Hacker News / 9 months ago
ArangoDB is a multi-model database that supports document, key-value, and graph data models with a unified query language. - Source: dev.to / 11 months ago
In modern databases, efficient data serialization and deserialization are paramount to achieving high performance. ArangoDB, a multi-model database, addresses this need with its innovative binary data format, VelocyPack. This article delves into the intricacies of VelocyPack, demonstrating its advantages, usage, and how it enhances the performance of ArangoDB with code examples in Java and Rust. - Source: dev.to / 12 months ago
ArangoDB: A native multi-model database, it offers flexibility for documents, graphs, and key-values. This versatility makes it suitable for applications requiring a combination of these data models. - Source: dev.to / about 1 year ago
ArangoDB, a "multi-modal" database engine that stores arbitrary JSON documents like MongoDB, key/value data like Redis, and graph relationships like Neo4j — and lets you leverage all three kinds of data in a single query. Source: over 2 years ago
Amazon SageMaker - Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly.
Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.
Deepnote - A collaboration platform for data scientists
MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.
Databricks Unified Analytics Platform - One platform for accelerating data-driven innovation across data engineering, data science & business analytics
OrientDB - OrientDB - The World's First Distributed Multi-Model NoSQL Database with a Graph Database Engine.
