pinot

Once you know what type of wine you're tasting, you can infer the price category: * French Pinot Noir is generally more expensive than New Zealand Pinot Noir.

For management of distributed state, it looks like Pinot depends on Apache Helix, which is an interesting framework.

Is the advantage of pinot that it is not as strict on data format as Druid (which requires json/delimited)...?

There are some red wines that can work where you'd normally go for a white, such as Pinot Noir.

Highest rated was a 6.99 Pinot Noir whose name escapes me at the moment.

Pretty soon Amazon will have it's own wine brand, a pinot noir.

I don't drink a lot of wine so I tend to just buy $14ish bottles of American Pinot Noir or Reislings.

I'm willing to accept someone can mistake a full bodied white for a thin Pinot Noir if food coloring was involved.

At a high level, the architecture seems to be very similar to Druid, although the Pinot team has yet to release more technical information about the project.

In terms of storage format, Druid enforces bitmap indexing and the Pinot docs appear to indicate that they have multiple types of indexes available, which is pretty cool.

Really like that LinkedIn uses Pinot at runtime.

The 2005 growing season in New Zealand was awesome and a lot of Central Otago Pinot Noirs for that season are unavailable, which drove the price up future seaons.

On the query API-side, it appears like Pinot exposes "PQL" which is a SQL-like query language.

What makes it confusing is that different kinds of wines have radically different flavor profiles: a Pinot Noir has a "lighter flavor" than a Cabernet Sauvignon.

That analogy doesn't account for what happens when a submission gets posted to both a "pinot" subreddit and a "sewage" subreddit, and subscribers in the sewage subreddit see the post in the pinot subreddit from the other discussions tab and "invade" the other subreddit.

Pinot ingests close to a Billion per day in real time and processes 100 million queries per day.

I think my wine drinking progression went something like Red Blush ($3bottle, or box wine)->White Wine->Merlot->Cabernet->Pinot Noir.

Pinot does use Helix, as it's been used successfully inside (and outside) LinkedIn to manage distributed state and coordination with a state model that's easily understandable.