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santafen

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DevRel leader and IoT guy [ my public key: https://keybase.io/davidgs; my proof: https://keybase.io/davidgs/sigs/cgr6s6NE0QTESqSAOdBrpfYqw693oKn6Ep38uVA1B_I ]

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This is like telling someone in Marketing "recompiling the linux kernel and turning on some new drivers is really simple. You don't even need to understand kernel architecture to do that."

Yes, it's simple for you, but for folks who just want to make sure that all their QR Codes reflect their brand, having to recreate that every time isn't worth it.

It's fine if this isn't your cup of tea.

It's the ability to customize the codes that you're paying for. Ad logos, and an almost limitless amount of customization. If all you want is standard black and white squares, that's easy and free all over the place.

Great question! Time series databases are a great solution for applications that need to process streams of data. IoT is a popular use case. DevOps and infrastructure monitoring applications as well. As has been mentioned in other comments here, there are a lot of use cases in financial services as well.

These are all applications where you’re dealing with streams of time-stamped data that needs to be ingested, stored, and queried in huge volumes.

QuestDB Head of DevRel here ... Yes, it can be a replacement of Postgres and it will be cheaper and faster. That being said, PGwire is still in alpha and is not 100% covered yet, so while migrating is possible, 100% Postgres Wire Protocol compatibility is not there yet.

For traditional transactional RDBMS data, I don't think it's a very common choice. For Time Series data, QuestDB is by far the fastest choice for Postgres-compatible SQL Time Series databases.

Here's a Medium post on Time Series Databases: https://medium.com/datadriveninvestor/what-are-time-series-d... But basically, they are databases where the time dimension is a critical aspect of the data. They handle never-ending streams of incoming time-stamped data. Think of streaming stock prices, or streaming temperature data from a sensor. You want to be able to query your data specifically in a time dimension -- let's see the temperature fluctuations over the past 24 hours, including the mean. Stuff like that.

A 'normal one' is typically used for things like transactional data which adds, deletes, and updates data among linked tables. While these transactions happen in time, the time component isn't necessarily a critical dimension of the data.

I like this bit a lot. Might have to extend it for QuestDB. I did a Notebook for QuestDB earlier this week, but having this part would be great!

Since you mentioned QuestDB ... I'm a former InfluxDB person, now at QuestDB. I'll say this about them: Their performance is off the charts good. Influx performance has been, frankly, headed in the other direction. I was looking at the NYC Taxi data the other day with QuestDB and I ran a sum over 1.6B rows of taxi data in under 150ms. 'select sum(passenger_count) from trips;'

IoT on QuestDB 6 years ago

Site owner here. There have been a couple of reports of being re-directed to ... call we say inappropriate material. So far I cannot reproduce this, and can see no reason why it might be happening. IF this happens to you, please feel free to reach out to me directly davidgs[at]davidgs[dot]com and I will work with you to get to the bottom of it.

IoT on QuestDB 6 years ago

Site-owner here. Went and checked everything. Can't find anything that would cause this, so please a) accept my apologies and b) give it one more shot. OR try dev.to/davidgs where it is reposted.

Can't believe that Sun SPOTs made it to Hacker News after all this time. I run the mirror site mentioned here, and still have a few drawers full of SPOTs (as well as a couple of complete kits in the boxes.

I was just talking to someone the other day about resurrecting the Squawk VM and porting it to the Cortex Mx architecture. It really was ahead of its time.