Understood that you dont;
But before Beyond/Impossible came, there used to be veggie patty that vegetarians enjoyed. And many of them have never tasted meat, and don't want to eat something that tastes like meat.
OP's point is that Beyond/Impossible replaced the veggie patty with a non-meat version of meat patty, instead of adding a new item in the menu.
And, honestly, as a meat-eater I really enjoy certain veggie patties. It's not meat, but it shouldn't be. They're their own delicious thing.
When I'm in the mood for a veggie burger, I don't want a hamburger. Restaurants shouldn't replace veggie patties with imitation meat -- they should have both.
The thing some vegetarians do not understand is that traditional cuisine from all over the World is basically 90% vegetarian, because poor people had to survive too.
I'm Italian, I could eat vegetarian meals everyday for a month without ever eating the same thing twice.
Same goes for all of Europe, Asia, Middle East, Africa or South America.
Vegetable dishes are the foundation of every established culinary tradition.
There's absolutely no need for incredible|magical|impossible|whatever meat.
> The thing some vegetarians do not understand is that traditional cuisine from all over the World is basically 90% vegetarian, because poor people had to survive too.
Sure, some people of every ilk are likely to be uninformed about some aspect of the world or the other. How does that apply in the current context? Most meals for most people worldwide are essentially vegetarian, even if the people are not obligate vegetarians. Are there some vegetarians unfamiliar with the reality of practically all world cuisines? Sure - and? Impossible meats aren't directed towards these people, and they aren't looking to substitute the taste of a burger. They're likely not averse to it, for what it's worth.
> Sure, some people of every ilk are likely to be uninformed about some aspect of the world or the other
I am absolutely not claiming that, I am absolutely claiming that beliefs based on feelings and not hard truths tend to reject rational arguments, hence their members are usually not the most curious people around and it's common they ignore things that are obvious to the rest of us.
Take a western vegetarian, we all know a few of them and some vegan too.
Most vegetarians/vegan inform themselves in vegetarian communities, which are based on the same western principles where they were born, mainly North America.
Most vegetarian communities are based on spurious correlations, like the fact that 80% of people from India are Hinduists, a religion that promotes a lacto-vegetarian diet letting people believe that 80% of Indians are vegetarians, which is obviously completely false.
Christianity promotes a mostly vegetarian diet too, there's a list of food that you should not consume on certain days, nobody follows those prescriptions anymore, they are thousands years old and come from the Jewish traditions.
But if I say that 30% of the World population is Christian, a religion that promotes a mostly vegetarian diet, things sound completely different.
Don't also forget that in vegetarian circles meat is the root cause of everything bad: from cancer[1] to diabetes[2], deforestation[3], being overweight [4], depression[5] and even infertility[6] (yes, you heard right!)
All these claims have been either debunked, highly exaggerated or correlated when there is no factual evidence. Yet they resist in the narrative of these communities, like the idea that Christ died on a cross and then came back to life 3 days later. It's false, we know it is, but people still believe it and there's nothing we can do about it.
It's easy to understand the stigma that these manipulatory lies can create around "traditional food", these people often think of themselves as revolutionary going against the status quo, so their enemy are their local traditions, not just the meat (everyone eats some meat around them, so it must be "the others their ways and they do not see it").
So they end up eating a lot of food that is not local nor traditional (tradition equals bad, remember?), such as tofu, that in Italy is totally not traditional nor commonly used, yet most vegetarians and vegans rely on it.
The reason why?
Vegetarianism in the west is a business, if you can sell the dirty cheap tofu at 5-10 euros/kg (that's the price in Italy) while poultry costs 3-5 euros/kg (raw, raised on the ground and antibiotic free) you can understand how convenient it is to sell people the idea that you need to eat tofu instead of pasta with tomato sauce (1-1.5 euros/kg), you are in for the big bucks.
Don't dismiss what I say just because you disagree, I've researched the topic a lot, this is just the tip of the iceberg.
> Most meals for most people worldwide are essentially vegetarian, even if the people are not obligate vegetarians
Sooner or later people in the west will understand that there are people among us priding themselves for not eating meat while our pets, for example cats, every year eat 10 times the meat an average central African person has to eat, suffering the horrendous consequences of malnutrition, like watching their children die of hunger or curable disease that their bodies weakened by the forced plant based diet hadn't the strength to fight, and we don't see a problem with that.
The irony is that those people are in developing countries, they are developing, they will eventually eat more meat, no way they will keep dying for a made up belief, for those who care about animal suffering I have an advice: renounce to pets. They eat too much meat, they kill too many animals, they are not sustainable.
I think you're conflating the median North American vegetarian with the median vegan. Your comment makes a lot more sense if I substitute "vegan" for wherever you've used "vegetarian". If you do indeed mean "vegetarian", then I think it makes much less sense in contemporary America, for example.
Yes, almost every vegan I've known is optimizing to minimize animal "cruelty", defined on their own ideological terms. Meanwhile, almost every vegetarian I've known is either one for religious reasons (and have their tradition's cultural cuisines to draw from) or simply don't like meat. I also know many Muslims who avoid meat at restaurants since it's not halal. I am struggling to recall any vegetarians that eat an average American diet by simply replacing meat with something like tofu.
If your intent is indeed to refer to vegetarians, I think that hasn't been the case in the US since perhaps the 90s. American vegetarianism really took off in the cultural context of the 60s and 70s, where Eastern ideas & sensibilities were imported but not the people or their cuisines. If a median American in the 70s wanted to maintain a meat free diet, their options were genuinely restricted. That's certainly not the case now, where the median American vegetarian is likely of recent immigrant descent, and has their heritage cuisine to inspire vegetarian meals. Changes to American immigration policy and the segment of countries where immigrants have come from have changed American vegetarianism. I also think something like Impossible burgers have very little appeal to the median vegetarian, since they're not interested in the taste of meat to begin with.
Yes, unlike the median American vegetarian, the median American vegan tends to appear spontaneously among families that are not themselves vegan. Unlike vegetarians, they don't have a rich family tradition to draw from, and plenty learn to just wing it. That said, I do think even this is likely not the case anymore. Today, in any big city, good vegan/vegetarian food is easy to find. As an illustrative example, I asked a relative who's lived in NYC for 40 years what his favorite restaurant meal has been (he absolutely loves steak). His favorite restaurant is a vegan Korean BBQ. Similarly, I've been informed by Mexicans of an amazing Mexican vegan place in Brooklyn.
Your second link validates my statement. You can absolutely trademark generic terms. There are limitations though.
Try to create a smartphone or computer company called Apple and see what'll happen. You can't trademark the word Apple for your apple farm because other apple farms must be allowed to use that word to describe their product.
That other companies have Apple in their name is not surprising. A trademark is not universal. There are so called classes and when you apply for a trademark you have to specify which classes you want covered.
Source: I went through this process and applied and was granted a trademark for my company. Other companies hold a trademark on the same term but in different classes.
Commitments and treaties can and have been broken throughout history.
The motivation to save the world from utter destruction gives greater reason than ever before to not start WW3... at least not over Ukraine.. treaty or no.
On behalf of a technology team, looking to incorporate a messaging platform to our landscape: I am curious to understand the motivation behind implementing a messaging system on top of a database technology. There are robust offerings both for small scale and large throughput systems. What are the benefits of this project over other implementations(RabbitMQ, Kafka, Celery, ActiveMQ, ZeroMQ, SNS/SQS)?
At my previous startup we put everything we could into the database (work queues and pup/sub included). It was magical.
It minimized complexity (moving parts, boundaries, etc...), everything was transactional, and a single dump of the database gave you a copy of the entire persistent state of your system at that moment (across all services).
We had several services running, but any notion of persistent state was stored in a single database. We didn't have particularly high demands, but processed ~140M jobs per month in addition to our normal query load.
Postgres handled this like a champ, had far lower p50 and p95 latency than SNS/SQS, and rarely went above single-digit percentage CPU usage on a fairly cheap DigitalOcean box.
I've worked at a lot of big tech companies (Google, Microsoft, Twitter, Salesforce) in many varieties of giant distributed systems and the most valuable lesson I've learned over and over again is: Distributed systems are hard, avoid them until you can't.
That's the best advice I can give to any startup. Until you're regularly sustaining 1,000's of TPS or have grown to dozens of TB of data, it is generally a distraction to even think about anything other than a single relational database.
That's great to read, and a perfect example of solving real problems instead of wasting time on exotic infrastructure.
The vast majority of companies and their scale will never go above a single midsize database server. All of the transactional, backup, and querying functionalities you list make it much more productive than using fancy AWS/cloud services.
We did a very similar thing where I used to work. Didn't want to bother with a separate task queue and wanted a consistent SQL interface for everything.
We wrote a very simple task queue (<500 lines of python) using a postgres table and inbuilt pub/sub. Ran millions of jobs, scheduled and unscheduled, without a hitch.
This! So many wasted years of engineering making correct applications on top of Cassandra/Kafka/Elasticsearch when a single Postgres server could have handled everything no problem.
Scalability for a tech product should be a concern at some point, but if you don’t have product market fit it doesn’t matter. The complexity of building a distributed system right out of the gate will cripple rapid iteration or lead to a broken product.
> put everything we could into the database (work queues and pup/sub included). It was magical.
I've been building systems on some pretty similar ideas for the last 5+ years, and have a similarly optimistic outlook on it. Just to add another datapoint here, we've been able to scale them up to 20-40x higher than your figure (a couple thousand jobs/sec) on a single (albeit beefy) MySQL instance. It definitely takes a fair bit of care & we certainly have some time invested in it, but it can be done.
I guess my services haven't had (gotten to? :-) ) to share databases with other services for quite some time -- they did when I started my job! -- but even with that concession, the benefits of DB guarantees have been amazing. There's nothing like a transaction for preserving your sanity.
The best tactic I've learned from these systems is to think really hard about the batching & partitioning behavior to keep msgs/sec high enough & transactions/sec low enough to stay afloat.
For some perhaps-off-topic contrarianism, what do you make of Uncle Bob railing against database-oriented architectures? [0] (He takes a good few minutes to get his point across.)
I've heard of him before but never really read anything much by him. Is this guy for real? He worked at one startup, got angry about a database, became a consultant, and screams about everyone being wrong about everything?
Yes he makes similar points there. A few scattered critical thoughts:
* I don't see any problem with stored procedures. They can make good sense for, say, auditing, as well as for performance.
* People describe their software systems as "Using Oracle" because it matters, not because their design is stupid. It tells me that Oracle skills are relevant, for instance.
* NoSQL is generally, in my experience, awful and chaotic, rather than liberating. Lots of good work has gone into making serious grown-up relational databases. Schemas, normal forms, constraints, rigorous work on the ACID properties. Something like MongoDB is just sloppy amateur-hour by comparison.
* In the YouTube video, he says that solid-state drives render relational databases obsolete. This strikes me as absurd. Not even ultra-fast SSD storage technologies will do that. The relational model is effective, and the associated DBMSs still well justified. Joins belong in a query language, not in imperative code. Why would you want to try managing a huge complex dataset manually?
I think the point is that you might be able to build something else than a standard relational db and make it faster.
Something like VoltDB but there are other solutions. There used to be some blogs about their architecture and how they could avoid a couple of steps a normal RMDB needs that takes a lot of time.
> I think the point is that you might be able to build something else than a standard relational db and make it faster.
I sincerely doubt that.
For it to be useful in real world situations, you'd have to build your own highly flexible, scalable, rock-solid, high-performance data-management solution, ideally one which enables the user to use a declarative means of expressing queries.
This is, of course, a DBMS.
If you build one which imposes structure on the data, you've got either a relational DBMS, or an object DBMS, or some other kind of well-studied database solution... except you've rolled your own from scratch, without input from database experts, so it's going to be a disaster.
Unless you're someone like Microsoft, Google, or Amazon, you pretty much can't build one of those. It costs tens of millions. It takes a huge amount of testing, for obvious reasons.
I really don't see any argument for not using a mature database system for managing a typical company's data.
Of course, if we aren't talking about a full-scale database that has to cope with a huge amount of messy mission-critical data in a changing business environment, then the game changes, and sure, you might have a chance just writing something yourself.
Netflix's video-streaming CDN ('OpenConnect'), for instance, obviously isn't powered by an RDMS. They put in a huge amount of highly technical work building their own finely tuned technologies to pull data off the disk and get it to the NIC with minimal glue in between. But that's Netflix, and virtually no real companies face that kind of challenge.
Also, VoltDB looks like a streaming DB technology. Isn't that both an DBMS (rather than a means of rolling-your-own), and very niche? I don't see how it's relevant here. If it's really able to serve business needs better, then great, but it's still a complex-DBMS-as-a-product.
I think his take on databases is moronic with a dash of common sense:
He rails against a strawman where people put SQL everywhere, into views, into application logic ("mail merge" is one he mentions), and DBAs gatekeep everything.
The common sense part: no, your views shouldn't be composing SQL with string interpolation.
The moronic parts:
- He venerates application logic and regards the data model as a detail, but data models aren't details — they tend to outlive application logic.
- He holds up in-memory data structures as a platonic ideal, but doesn't address the things databases provide for you: schemas, constraints, transactional semantics and error recovery, a clear concurrency story.
Not OP, but we do something similar it our startup. PostgREST (http://postgrest.org) definitely helps if you want to go down this path as it exposes everything in the database (including functions etc) via a RestFUL api.
Of course, at the point where you do need to break out beyond a single DB, life is more painful because you've got dependencies on the database all over the place...
If you put everything in the database, and use it for all it's able to do, as the comment I replied to suggested, it is practically inevitable under startup feature pressure conditions that total modularity won't hold. And in fact I think it would be irresponsible to pursue total modularity; it would court failure.
I believe you're being deeply naive about modules owning single tables. You forego relational integrity and almost the whole power of relational algebra if you take that approach. That's heaps of functionality to leave behind when you and one or two other guys need to crank out a feature a day.
You obviously need to write queries which span tables (I.e. joins).
I can see how you misunderstood me there however, it was admittedly poorly worded.
What I was talking about was basic data hygine as it's often called.
If you need specific data, you define a clear way to get this data and only access it through that API. This can be a class, method or anything your language of choice prefers.
If you skip that step and directly access the DB everywhere in your code, you'll create another unmaintainable dumbsterfire as soon as your team goes beyond the initial programmers.
Having scaled up the tech in a company from $0 to $10+MM ARR, from zero customers to over 300 million records a day, I think you are simply incorrect and uninformed about the trade-offs that make sense in a startup.
You hit on the real reason architects push microservices in smaller companies: it limits options to engineers and to the startup by putting up walls in the form of network rules that are resistant to change.
A startup needs all the options on the table because the alternative is they go out of business and there is no startup. This idea that we can enforce “good architecture” (subject to interpretation) with technology by isolating junior engineers with networking rules needs to at least be more transparent about its motivations.
Services permit scaling development teams. In a startup where you're all in the same room, lots of separate services don't really make sense, and you probably don't know where to make the right cuts even if you tried. When you want to grow beyond the one big room, with a lot of teams, potentially in other time zones and countries, then you want to be able to carve off services so teams can own them.
The problem here is that an unmitigated monolith with no domain partitioning in its data model can't be transformed into a service architecture by carving off pieces.
For pieces to be able to be carved off, they already have to be autonomous.
What usually happens is that devs without experience in service architectures presume that service architectures are probably just the things they are used to seeing, ie: monolithic entities.
It's usually then that we hear things like "extract the product service". The problem is that product is an entity, and entities are the last thing to build services around. That's how we end up with distributed monoliths, and subsequently failed service architecture projects.
In order for an app to be able to transition to services, the app has to be designed this way from the beginning.
And yes, it's definitely possible to know what the model partitions should be up front. They're very natural divisions. But they can't be arrived at by looking through an entity-centric lens. And unfortunately, forms-over-data apps very rarely provide us with an opportunity to learn about the "other" way to do it.
Message DB happens to be implemented using a RDBMS, but the streams in it end up being very clear partition points. Some thought would be required to move data to a different database, but an event-sourced model isn't the same as coupling through a traditional RDBMS schema.
Or managed Postgres on AWS Aurora, AWS RDS, Google Cloud SQL, Heroku, etc :)
SNS, Kenesis (Kafka), Google Pub/Sub are awesome. Not the same problem/solution fit as an event store, but awesome for the scenarios and architectures they're targeted at.
Is there a difference from a programming perspective between, say Kafka, and the event store linked in this post?
I understand that Kafka can scale horizontally and can handle crazy throughput, but I mean from a programming point of view, the idea of a unified log as a data model applies to both, correct?
There are some similarities, and there are definitely worse technologies you could choose for a message store than Kafka. It's worth calling out the difference between event-sourced and event-based. The former is necessarily the latter, but that doesn't go in the opposite direction.
Event-based just means that communication happens over events. Event-sourced means that the authoritative state of the system is sourced from events. If the events are literally the state, then how those are retrieved begins to matter.
Kafka breaks down as a message store in 2 key ways that I mentioned elsewhere in all these threads.
> The first is that one generally has a separate stream for each entity in an event-sourced system. Streams are sort of like topics in Kafka, but it would be quite challenging to, say, make a topic per user in Kafka. The second is Kafka's lack of optimistic concurrency support (see https://issues.apache.org/jira/browse/KAFKA-2260). The decision to not support expected offsets makes perfect sense for what Kafka is, but it does make it unsuitable for event sourcing.
If my only tool were Kafka, then I wouldn't be able to use the messages in the same way that I can with something like Message DB. And that's okay, different tools for different jobs.
The technologies you listed are message brokers, while Message DB is a message store. The former transport messages, and the latter is a database specialized for storing message data and sourcing system state from those messages. Kafka can, for example, move a lot of events around, but it isn't suitable for event sourcing for 2 key reasons.
The first is that one generally has a separate stream for each entity in an event-sourced system. Streams are sort of like topics in Kafka, but it would be quite challenging to, say, make a topic per user in Kafka. The second is Kafka's lack of optimistic concurrency support (see https://issues.apache.org/jira/browse/KAFKA-2260). The decision to not support expected offsets makes perfect sense for what Kafka is, but it does make it unsuitable for event sourcing.
Being built on top of Postgres, Message DB gives you access to event sourcing semantics using a familiar database technology.
We use Message DB in our production systems, and I'd be happy to talk more about it if you have other questions. We've found it very reliable.
As a disclaimer, I'm listed as a contributor at the Eventide Project, the project Message DB was extracted from, though I did not write any of the code behind Message DB.
I think the biggest difference is that it’s a Message Store as highlighted by the preceding comment.
Some clarity by example: In financial systems, it’s extremely important to keep track of all the transactions between your microservices (if your architecture is based on that). You could potentially lose a message delivered to you via a broker if your service fails to write it to a persistent storage. If the producer of that message never stored that message or it was produced on wire and transmitted, there is no way to recover it anymore. A system designed around a Message Store can mitigate such problems. You can build that similar architecture with brokers as well but for each of your application, you will have to implement something analogous to a Message Store to handle idempotency and things like that.
Incorrect. Kafka is a message _storage_. The server can be seen as a distributed persistent append-only log. All broker logic is encoded in the client. Source: maintainer of one of client implementations.
Depends on your requirements, and the message throughput, but we have had great success using a database as a message broker. We get atomic commits on jobs, audit history, database backup is all we need for recovery, and a less complex stack. We did use RabbitMQ, but replaced it with using SQL Server, and the sql notifications to make it efficient. Couldn't be happier, but we only do thousands of messages a day, not sure I'd use the same approach with millions.
I think the sentiment here is not acknowledging the full picture of shift in car ownership in US.
While it is true that more families are opting for SUVs, but that is because more families are opting to share a car (preferably an SUV from utility perspective) rather than owning two or more cars/sedans. The increase in availability of rideshare (Uber/Lyft) is also playing a part in this gradual shift.
(I can't seem to find the study which stated above, but will keep looking and update this comment when I find it)
Interesting idea. It would be a learning opportunity for all of us to know what libraries/frameworks are being used to create these website. Maybe this is something you can add to the aggregated feed.
Also, quite a few of them seem to be down. I would suggest marking them as inactive.
My first impression is that I am more receptive to ideas related to Fitness (and eyes), but not so much about Diet.
That maybe specific to my own lifestyle choice, but I find dietary plans too intrusive and lacking in context(my health, dietary needs, food availability etc).
Below are two questions that I ask myself, when I need to do a task I do not feel like. My experience has always been that the impedance is higher at only start of the task, and if the answer to any of below two questions is Yes, then the value of outcome would supersede my initial uneasiness.
1. Would the value created by this task reduce over time? In other words, is it better to do this task today than in future?
2. Does the effort required by the task increase (or remain same), if delayed? In other words, is it easier for me to do this task today than in future?
In the case, where answer is No to both the questions, I have come to terms with being comfortable with procrastinating on that task.
If I cannot convince myself of value added vs effort required today vs in future, it is okay to delay the task.
Also, choosing not to do a task now and procrastinate can be a powerful and useful tactic.
