I love this comment, but presumably there's a need for databases that are well suited for write heavy workloads. Also there's no great story for starting out with an RDBMS and then scaling out. Right now if you're with MySQL you have some options to scale out with read replicas, and then eventually replicate to a TiDB cluster. PostgreSQL I guess there's cockroachdb, but it's kind of meh.

I believe Cloudflare usage of PostgreSQL is "write heavy" and is a RDBMS that scaled out very well for them.

They are using CitusDB but it's still RDBMS and support most PostgreSQL SQL query without the need to rewrite your query or change your schema.

They moved to Clickhouse recently, though: https://blog.cloudflare.com/http-analytics-for-6m-requests-p...

In fact Youtube for a long time was running on MySQL with a tiny service called "vitess" on top of it to handle (Sharding/partitioning) automatically.

I dont know if they are still using Vitess or migrated to Google other relational Database "Spanner"

YouTube switched some Vitess workloads over to Procella. http://www.vldb.org/pvldb/vol12/p2022-chattopadhyay.pdf

In general I've noticed that people outside Google assume that Spanner is much more popular than it really is.

To be honest I am surprised its not more popular.

if you work at google and its one of the option to choose from! Is there any reason to "not" choose spanner for new project and instead use something else?

It's expensive.

Something something bigtable

That's true, I forgot about Citus.

You remind me of some ex coworkers who thought everything could be done on RDBMS systems and then when they had to export large amounts of data topped out at 3500 tps.

Meanwhile I'm over here using Scylla and 3 nodes can give me roughly 3.5M TPS for data extraction.

RDBMS are great for certain use cases but they do not scale and if you think they do you don't really know what scale means.

Sure you can cite things like Github using MySql, but i'll also point out they've invested thousands upon thousands of man hours customizing layers on top of MySql to support their sharding which also, oops, had a bug that gave them almost half a day of downtime at one point. This is not a good use of someone's time, GH definitely made the wrong decision. Don't steer other people into making similar mistakes especially given it seems you have a lack of experience on designing systems at scale.

Exactly where did I suggest using a single mysql instance or bandaiding a fleet of them together?

Clickhouse vastly outperforms and outscales Scylla with a fraction of the hardware and cost.

Different purposes — OLAP vs. OLTP. Reminder of this thread:

https://news.ycombinator.com/item?id=22478407

Clickhouse is in no way an RDBMS.

R doesn't stand for row-store. The access patterns of Clickhouse are comparable with any RDBMS. The fact that it happens to be a column-store doesn't make it not an RDBMS. It doesn't mean "row-oriented databases designed for OLTP workloads" as it appears you think is the case.

Should I have simply said "SQL databases where data is represented in tables with a defined schema" to simplify the discussion and prevent your ignorant diatribe?

It stands for "relational", you know that CLickhouse is not a relational database right?

Have you used any of these technologies? Cassandra/Scylla have a defined schema. Did you really not know that?

There are other requirements other than low-volume transactional data and CRUDs...

I’m guessing your usage of a RDBMS hasn’t extended beyond an ORM library.

I'm obviously being hyperbolic, not sure about you. Point remains that scaling RDBMSs is not exactly trivial and it does look like most companies eventually give up.

Eh, there are numerous options today (vitess, citus, clickhouse, aurora, redshift, bigquery, snowflake). Clickhouse outperforms Scylla by a wide margin at a fraction of the cost and complexity.

Any of the above makes your data accessible via standard SQL. You can hire and utilize proficient data analysts, not people writing esoteric queries in whatever flavor of NoSQL, while actually solving business needs.

Not sure what you're talking about then? It seems you're just talking about the syntax used to query (which I agree SQL is a no-brainer) and not really about the "R" in "RDBMS"

You haven't made a point yourself, so honestly, I don't fucking know what we're talking about either. You came in with a hyperbolic comment that echoes the stance from the NoSQL community I've seen for the past decade. The one that basically says "We have zero fucking clue how to model our data so we're just going to jam everything into bunch of loosely connected JSON documents and spend the next decade adding basic SQL features from the 70s".

I'm not a native speaker but I dare say the point itself about RDBMS was pretty clear. I don't really feel like continuing this argument either.

Clickhouse and other solutions you mentioned are for analytics while Scylla and Cassandra are for real-time. You can't compare the two types of tech

I don't see how Scylla / Cassandra are real-time but ClickHouse is not. You can load event data into ClickHouse just as fast as Cassandra. The data are instantly queryable including pre-computed aggregates in materialized views. You can get answers in milliseconds on data that is only a few second old. Real-time marketing is now an important use case for ClickHouse, just to give one example. If the problem is analyzing and reacting to external events, ClickHouse is tough to beat.

How are Scylla / Cassandra better?

clickhouse, bigquery, snowflake are not even close to RDBMS so what are you going on about? Have you actually used any of those?

is there a way to have a short private chat? I am an AppSec Engineer. Really max 10 minutes of your precious time.