log4shell

That answers my question, thanks! Ordering does not matter part has me curious too, I will read other comment and come back to you l.

I am not aware of any such implicit connection of ledger and commutative property, also couldn't find anything as my google-fu is letting me down. Anything I can refer to? Generally curious to know use of term ledger outside of accounting and blockchains.

I have seen it used to mean WAL before, so I am taking this with a dose of skepticism.

Calling a WAL a ledger, why? Ledger sounds fancier but why would it be a ledger in this case?

Good call-out, should have named the query engines lagging behind too!

I am wondering how portable is parquet format and how interchangeable it is now?

It is refreshing to see multiple projects with arrow/datafusion trying to bank on existing and user friendly spark's API instead of reinventing the API all over again.

There is likes of comet and blaze that replace execution backend of spark with datafusion and then you have single process alternatives like sail trying to settle in "not so big data" category.

I am watching evolution of projects powered by datafusion and compatible with spark with keen eye. Early days but quite exciting.

What is your use case?

Congratulations to duckdb team! Can't wait to try some of the newly released features and performance improvements.

I am quite curious about the plans for python dataframe like API for duckdb, and python ecosystem in general.

Its great to have a single entrypoint for multiple backends. What I am trying to understand and couldn't find much information related to: How does the use of multiple engines in Ibis impact the consistency of results for the same input and query, particularly in relation to semantic differences among the engines?

Is there a way for general public to see the status of open sluice gates and water levels in various parts of netherlands? A live datastream might be the best!

Druid has quite some intelligence baked in to handle the scaling by default. I am curious how clickhouse is doing in all those aspects.

When we did a PoC, the operational aspect of clickhouse and performance was severely lacking as compared to druid. Clickhouse had bigger resources at its disposal than druid during this PoC.

If they could improve the operational aspect and introduce sensible defaults so that the users don't have to go through 10000 configuration to work with data in clickhouse, I am sure I will give it a go for some other usecase. It is simple on surface but devil is in the details. Druid is much simpler and sane at the scale I need to operate.

Kafka is not vulnerable for this particular exploit but hdfs kafka connect plugin is.