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HTAP is Dead

mooncake.dev

91–95 of 95 posts

Re: HTAP is Dead

#91

> Most workloads don’t need distributed OLTP. Hardware got faster and cheaper. A single beefy machine can handle the majority of transactional workloads. Cursor and OpenAI are powered by a single-box Postgres instance. You’ll be just fine. I thought this was such an important point. Sooooo many dev hours were spent figuring out how to do distributed writes, and for a lot of companies that work was never needed.

Something tells me neither cursor nor openai need write workloads, so they would probably do just as fine using a flat file. I'm honestly curious what use either would have for queries that you couldn't get with a filesystem. Certainly neither products have much obvious need for OLTP workloads. Hell, neither have any need for transactions at all. You're just paying them for raw CPU.

Update: in my mind, this reflects analytics of queries. Just further reason to run your own models I guess....

Re: HTAP is Dead

#93
One thing none seem to notice is the rise of “Operational Warehouses” such as RisingWave or Materialize. A big ‘problem’ in OLAP, as the article mentions, is people expects aggregations or analytic views on live data. These solutions solve it. In principle, this shows that just having incrementally maintained materialised views, really goes a long way towards achieving the HTAP dream on a single DB.

Re: HTAP is Dead

#94
I stopped reading early, when the article said that in the 1970s one big relational database did everything.

In fact, relational databases did nothing in the 1970s. They didn't even exist yet in commercial form.

My first prediction as an analyst from 1982 onwards was that "index-based" DBMS would take over from linked-list DBMS and flat files. (That was meant to cover both inverted-list and relational systems; I expected inverted-list DBMS to outperform relational ones for longer than they did.)

Re: HTAP is Dead

#95

Earlier quoted context omitted.

Something tells me neither cursor nor openai need write workloads, so they would probably do just as fine using a flat file. I'm honestly curious what use either would have for queries that you couldn't get with a filesystem. Certainly neither products have much obvious need for OLTP workloads. Hell, neither have any need for transactions at all. You're just paying them for raw CPU.

Update: in my mind, this reflects analytics of queries. Just further reason to run your own models I guess....

It's not just analytics. ChatGPT saves all of your conversation history - I don't know if they save the full conversation text in postgres, but I'd assume they at least save conversation metadata there.

You may not want this from a privacy perspective, but as a user I find it to be a very useful feature, e.g. I can see my full history, I can easily share conversations with a share link (and it's the exact version of that conversation, not like a URL where contents can change).

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