Saturn Cloud
Deepnote
Apache Zeppelin
Amazon SageMaker
Databricks Unified Analytics Platform
Azure Synapse Analytics
Google BigQuery
GeoSpock
Redis
MongoDB
ArangoDB
Apache Cassandra
PostgreSQL
neo4j
memcached
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.
Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache and message broker. It supports data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes with radius queries and streams. Redis has built-in replication, Lua scripting, LRU eviction, transactions and different levels of on-disk persistence, and provides high availability via Redis Sentinel and automatic partitioning with Redis Cluster.
Saturn CloudSmooth 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.
Based on our record, Redis seems to be a lot more popular than Saturn Cloud. While we know about 189 links to Redis, we've tracked only 6 mentions of Saturn Cloud. 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.
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 1 year 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 1 year 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 1 year 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 2 years ago
At the moment I am going to go to https://saturncloud.io/ or https://www.cloudeo.group/. Source: over 2 years ago
Redis is an open-source, in-memory key-value data store known for its speed and performance. It supports various data structures like strings, lists, sets, and hashes. - Source: dev.to / about 3 hours ago
Valkey is an open source alternative to Redis. It's a community-driven, Linux Foundation project created to keep the project available for use and distribution under the open source Berkeley Software Distribution (BSD) 3-clause license after the Redis license changes. - Source: dev.to / 11 days ago
Many popular open source projects are beloved and closely tied to particular vendors. For example, web frameworks like React and Angular are associated with Meta and Google, respectively. Database software like MongoDB, Elasticsearch, and Redis are also tied to specific commercial entities but are widely used and praised for their functionality. When there is a clear driver of a project, it can offer some benefits:. - Source: dev.to / 12 days ago
One of the most effective ways to improve the application’s performance is caching regularly accessed data. There are two leading key-value stores: Memcached and Redis. I prefer using Memcached Cloud add-on for caching because it was originally intended for it and is easier to set up, and using Redis only for background jobs. - Source: dev.to / 22 days ago
Hi there! I want to show off a little feature I made using hanami, htmx and a little bit of redis + sidekiq. - Source: dev.to / about 2 months ago
Deepnote - A collaboration platform for data scientists
MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.
Apache Zeppelin - A web-based notebook that enables interactive data analytics.
ArangoDB - A distributed open-source database with a flexible data model for documents, graphs, and key-values.
Amazon SageMaker - Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly.
Apache Cassandra - The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance.
