This looks awesome! I’m not an expert but wouldn’t the typical database hardware not be really optimal for running ML? Is this meant to run on a replica (which is quite straightforward to setup) that has ML optimised hardware?
Show HN: PostgresML, now with analytics and project management
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Re: Show HN: PostgresML, now with analytics and project management
#22Earlier quoted context omitted.
None, it's just an extension. Which is part of what is so awesome about PostgreSQL, everyone can build extensions that look and feel native and can do almost anything.
You might want to use a different elephant logo... the branding implies that it is an official part of the project. E.g. Postico uses an elephant but not the _same_ elephant - https://eggerapps.at/postico/
I think the logo is clever, and if there’s no rights issue it’s great. The fact that it’s a different website, domain, theme etc doesn’t make it ambiguous IMO
Re: Show HN: PostgresML, now with analytics and project management
#23This looks awesome! I’m not an expert but wouldn’t the typical database hardware not be really optimal for running ML? Is this meant to run on a replica (which is quite straightforward to setup) that has ML optimised hardware?
It’s probably a stretch to run GPT-3 inside a db, but most of the “deep learning” models I’ve run in more traditional environments are a few megabytes. That’s millions of params, but Morre’s law has been generous enough to us over the decades that I think there is a good case to spend a few megabytes of DB ram on ML. I would think this idea has really landed though, when we start hearing about Postgres deployments with GPUs on board though :)
Re: Show HN: PostgresML, now with analytics and project management
#24What affiliation does this have with PostgreSQL?
None, it's just an extension. Which is part of what is so awesome about PostgreSQL, everyone can build extensions that look and feel native and can do almost anything.
You should review the PostgreSQL trademark policy: https://www.postgresql.org/about/policies/trademarks/
Re: Show HN: PostgresML, now with analytics and project management
#25Do you plan on adding support for managed PostgreSQL services like RDS in the future?
We can’t control the extensions RDS allows to be installed, and they are historically conservative. Lev and I do have some fairly extensive experience with replication patterns to Postgres instances running in EC2. Foreign data wrappers are also an option, and depending on workload may be a good horizontal scaling strategy in addition.
Will that also apply to plans? I'd love to see ML models come up with better plans, if possible.
Re: Show HN: PostgresML, now with analytics and project management
#26No post body was provided.
Re: Show HN: PostgresML, now with analytics and project management
#27Do you plan on adding support for managed PostgreSQL services like RDS in the future?
We can’t control the extensions RDS allows to be installed, and they are historically conservative. Lev and I do have some fairly extensive experience with replication patterns to Postgres instances running in EC2. Foreign data wrappers are also an option, and depending on workload may be a good horizontal scaling strategy in addition.
I just gave it a try to install on Crunchy Bridge [1], disclaimer I work at Crunchy Data. I did this as a standard user vs. anything special about access. I got quite close, but looks like I'm limited by Python version, we give you plpython3u with Python 3.6. Is there any chance of supporting an earlier 3.x version? If so I'm pretty sure could give a guide on how to self-install on top of us.
Re: Show HN: PostgresML, now with analytics and project management
#28Hello really nice ! Can you explane the differences with https://madlib.apache.org/ ? Wouldnt an OLAP db better suited than pg for this kind of workload ? Does being a postgreSQL module make it compatible with citus, greemplum or timescale ?
OLAP vs OLTP will depend on your ML use case. Online predictions will likely be better served by an OLTP vs offline batch predictions being better served by OLAP.
OLAP use cases often involve a lot of extra complexity out of the gate, and something we're targeting is to help startups maintain the simplest possible tech stack early on while they are still growing and exploring PMF. At a high enough level, it should just work with any database that supports Postgres extensions, since it's all just tables going into algos, but the devil in big data is always in evaluating the performance tradeoffs for the different workloads. Maybe we'll eventually need an "enterprise" edition.
Re: Show HN: PostgresML, now with analytics and project management
#29This is awesome. I’m guessing the models are executed on the database server and not a separate cluster? What about GPU training? How is that handled? I’d love to see more docs.
Re: Show HN: PostgresML, now with analytics and project management
#30Earlier quoted context omitted.
We can’t control the extensions RDS allows to be installed, and they are historically conservative. Lev and I do have some fairly extensive experience with replication patterns to Postgres instances running in EC2. Foreign data wrappers are also an option, and depending on workload may be a good horizontal scaling strategy in addition.
I just gave it a try to install on Crunchy Bridge [1], disclaimer I work at Crunchy Data. I did this as a standard user vs. anything special about access. I got quite close, but looks like I'm limited by Python version, we give you plpython3u with Python 3.6. Is there any chance of supporting an earlier 3.x version? If so I'm pretty sure could give a guide on how to self-install on top of us. [1] https://www.crunchyd…
Awesome. I'll see what it'll take to get the extension running w/ Python 3.6. It's good to know what people's ecosystem dependencies look like.