Deepseek is the real "open<something>" that the world needed. Via these three projects, Deepseek has addressed not only efficient AI but also distributed computing:
how many companies will actually adopt 3FS now that it's open source?
not a hater, just know that theres a lot of hurdles to adoption even if something if open source - for example not being an industry standard. i dont know a ton about this space - what is the main alternative?
to me this seems to target a pretty small audience: very big data and specific problem domains, you need killer devops chops, expensive & specialized infrastructure and a desire to build out on bleeding edge architecture. I'd suspect most with these characteristics will stick with what they've got, "medium Big Data" companies should probably go with hsoted services and the rest of use stick with a single node DuckDB.
Bingo. Very few organizations have petabytes of data on which they are trying to efficiently process for machine learning. Such organizations already have personnel and technology in place offering some kind of solution. Maybe this is an improvement, but it is quite unlikely to be offering new capabilities to such teams.
For example, in AWS, you can get a similar FSx for Lustre file system for just 11% more cost, which could be worth it to avoid the management costs of running your own storage cluster.
At least there hasn't been anything for distributed DuckDB before it afaik. For anyone with a substantial DuckDB project, they might now go distributed without having to rewrite it in something else.
Was it already happening when platforms started supporting stuff like Iceberg? But is kinda nice to see things like Snowflake have definitely their place on the ecosystem but too often at margins especially with huge workloads Snowflake creates more issues than solves them
Were you there when we had to work with our data in Teradata and SAS and hundreds of multi hundred MB Excel spreadsheets containing analytical data? 30+ minute queries were the norm. Snowflake was a breath of fresh air.
Yes, not saying this is bad at all, just kind of funny. When you think about it it makes sense though. Why wouldn't want someone have a possibility to distribute an efficient engine.
These type of models need to be trained across thousands of GPUs, which requires distributed engineering on a much higher level than "normal" distributed systems.
This is true for DeepSeek as well as for others. There are a few companies giving insights or open-sourcing their approaches, such as Databricks/Mosaic and, well, DeepSeek.
The latter also did some particularly clever stuff, but if you look into details so did Mosaic.
OpenAI and Anthropic likely have distributed tools of even larger sophistication. They are just not open source.
spark is getting a bit long in the tooth.. interesting to see duckdb integrated with Ray for data-access partitioning across (currently) 3FS. probably a matter of time before they (or someone) supports S3. It should be noted that duckdb (standalone) actually does a pretty good job scanning s3 parquet on its own.
1. smallpond: https://github.com/deepseek-ai/smallpond
2. 3fs: https://github.com/deepseek-ai/3FS
3. deepep: https://github.com/deepseek-ai/DeepEP