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Doesn't JVM here result in some amount of "dicking around" with respect to which JVM language to use? Or do you mean that it doesn't matter, as long as it's all

Doesn't JVM here result in some amount of "dicking around" with respect to which JVM language to use? Or do you mean that it doesn't matter, as long as it's all JVM? Or do you mean to just pick java? One thing I've seen in my experience generally buying this "standardize on boring tech" take, is that it's really common these days for a company to be doing some amount of "serious" data science work, and most people seem to really want to do that in python, and it also seems to benefit pretty significantly from some kind of OLAP database system. So adding those things onto your "boring" stack becomes JVM+psql+k8s+python+snowflake/databricks/duckdb(?). But I agree with your real point about serverless.

jpgvm 4y ago
Generally speaking your data-science stuff wouldn't fit into the serverless bucket anyway though. Also generally Python is just used for terminal processing in the Big Data world, all the pieces in between are JVM anyway.
- disgruntledphd2 4y ago
  Yeah, I mean if you're already a JVM shop then you could probably run Spark yourself (which can be painful) and use SparkSQL to dump to Python (maybe on databricks, though I'm not a massive fan) and do your fancy ML stuff there. Alternatively, you could just use a read-only PG replica and Python here, which would suffice for most DS needs (unless your core product is DS related or you have huuuuuggggggggeeee data (which you probably don't)).
  - jpgvm 4y ago
    Yeah that is fair too. Most people have tiny data. Then there is places I have worked... where 10TB qualified as small data that you "just query with Presto" and where more exotic things were needed for actually interacting with the "big data". All relative in the end.
    - disgruntledphd2 4y ago
      Yeah, snowflake is super nice for analytics, but PG will get you a long way with less complexity (given that you're already using it for OLTP).
- sanderjd 4y ago
  This doesn't mesh with my experience of the current breakdown in usage between python and the jvm for these use cases.
vbezhenar 4y ago
For backend, JVM implies Java. Although Kotlin is safe choice as well, it's not as popular so I wouldn't suggest to use it, unless you have good reasons to (like team of Android developers who decided to build backend).
- jpgvm 4y ago
  I actually use Kotlin. :) I am happy with either Kotlin or Java though. Reasons for Kotlin is mostly nullability typing though @NotNull gets you pretty far in Java these days with the tooling configured correctly. I like the syntax a bit more and extension functions are a nice sugar vs util classes with static functions. The main reason however is I have a lot more luck convincing Typescript developers to try Kotlin than Java which is relevant when most of my colleagues have primarily done Typescript. Either or though IMO, both are great choices for backend development and they interoperate really well.
- sanderjd 4y ago
  > For backend, JVM implies Java. ... no it doesn't.

jpgvm 4y ago

Generally speaking your data-science stuff wouldn't fit into the serverless bucket anyway though. Also generally Python is just used for terminal processing in the Big Data world, all the pieces in between are JVM anyway.

disgruntledphd2 4y ago
Yeah, I mean if you're already a JVM shop then you could probably run Spark yourself (which can be painful) and use SparkSQL to dump to Python (maybe on databricks, though I'm not a massive fan) and do your fancy ML stuff there. Alternatively, you could just use a read-only PG replica and Python here, which would suffice for most DS needs (unless your core product is DS related or you have huuuuuggggggggeeee data (which you probably don't)).
- jpgvm 4y ago
  Yeah that is fair too. Most people have tiny data. Then there is places I have worked... where 10TB qualified as small data that you "just query with Presto" and where more exotic things were needed for actually interacting with the "big data". All relative in the end.
  - disgruntledphd2 4y ago
    Yeah, snowflake is super nice for analytics, but PG will get you a long way with less complexity (given that you're already using it for OLTP).
sanderjd 4y ago
This doesn't mesh with my experience of the current breakdown in usage between python and the jvm for these use cases.

vbezhenar 4y ago

For backend, JVM implies Java. Although Kotlin is safe choice as well, it's not as popular so I wouldn't suggest to use it, unless you have good reasons to (like team of Android developers who decided to build backend).

jpgvm 4y ago
I actually use Kotlin. :) I am happy with either Kotlin or Java though. Reasons for Kotlin is mostly nullability typing though @NotNull gets you pretty far in Java these days with the tooling configured correctly. I like the syntax a bit more and extension functions are a nice sugar vs util classes with static functions. The main reason however is I have a lot more luck convincing Typescript developers to try Kotlin than Java which is relevant when most of my colleagues have primarily done Typescript. Either or though IMO, both are great choices for backend development and they interoperate really well.
sanderjd 4y ago
> For backend, JVM implies Java. ... no it doesn't.