261 karma · joined November 27, 2017
That was 4.4 million people, even before the vaccine mandate was around.
As for the first question - I've tried using Neo4j and ArangoDB for relatively large-scale graph querying (1-2TB of data) and both couldn't hold a candle to Postgres or MySQL in terms of query performance for cost. Neo requires you to store most of your data in memory and Arango isn't great for cross-shard querying.
Unless there's some major new graph DB that comes out in the next few years I would still bet on relational being dominant in 2030.
As far as free speech platforms go you have things like Gab, Voat, etc which prioritize free speech in name. While that may be commendable as a value, the core audience they attract in the beginning is inevitably too extreme for the platform to go mainstream.
By the time Reddit replaced Digg, Digg was already losing users routinely. I don’t think any of the current social media players are in that position just yet.
I'm not sure where the P2P interactions will go - it's possible that they stay centralized on the major platforms of today, or we see a return to smaller forums as we had back in the late 90s and early 2000s.
I sincerely believe that the leadership tried to avoid the ads revenue stream and all the ills that come with it for as long as possible, and searched for a lot of ways out (see things like Reddit Notes in the past). But I don't think I'll work in the social media domain again, because the experience really soured me on the sustainability model as a whole. People are generally unwilling to donate/pay for the content, and it's impossible to operate a site where there's no subscription revenue coming in.
Prior to ads and the current dark patterns you see on the site, Reddit primarily tried to monetize through Reddit Gold. It didn't work, and users never purchased it in any meaningful volume to keep the site afloat. So while you wouldn't give them money for the decisions they've made recently, they weren't making enough money when they were (ostensibly) making better decisions.
How would you go about solving this problem? It's a genuine question without snark - if social media companies are unable to stay sustainable through direct user funding, then they're going to look to ads or other sources eventually.
While I think you're absolutely right, I think Digg made a number of other missteps with the Digg v4 launch that Reddit did not make. In particular, they shut down the old Digg site to reuse the servers for the new one, a mistake that Reddit was particularly careful not to make.
Digg was also already on the way down before their failed launch, and before the exodus to Reddit - a condition that doesn't apply to Reddit today. People have been making Digg comparisons about Reddit before I worked there, and now long after I've left. I don't think the 2 are comparable.
Will Larson writes about it here: https://lethain.com/digg-v4/
Fox has been going more to the right for a few years now, but CNN has really been fading out especially with the recent scandals hitting Chris Cuomo and Don Lemon. Their core audience is older centrist-leaning folks and securing someone like Chris Wallace may help them bring over some center-right viewers from Fox.
Article quote:
> We just closed a $68M Series B co-led By Lux and Tiger Global, with participation from Greenoaks Capital Partners, Lightspeed, Addition, and Haystack.
Sure, there are certainly people who exclusively used CSS in JS, but I would hardly say that they are even a majority of frontend devs.
In contrast, connection poolers like Odyssey or pgbouncer live external to your applications, meaning that:
1. You can connect to them from any application written in any language (not just Python) 2. They provide a global pool for all of the applications connecting and help to not overload Postgres.
So let's say their annual revenue is 3-4x since ad spend is usually weighted heavily towards Q4. At 300-400M per year and growing that's actually pretty solid.
I assume you mean "Kafka Streams" when you say this, as Kafka is just a event bus and Flink can be used to read messages from it.
The biggest advantage of Flink (IMO) is that you can write the Flink logic once, and reuse it for both batch and stream processing. So if I write a Flink job that consumes a Kafka stream and produces some aggregated outputs, that same job can be run against my data lake in S3/GCS/Azure Blob Storage, etc.
Kafka Streams does not support batch processing, or working on top of anything other than Kafka. Flink supports building on top of other message buses like Pulsar as well: https://flink.apache.org/news/2019/11/25/query-pulsar-stream...