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Dgraph, GraphQL, Schemas, & CRUD – Ardan Labs

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Re: Dgraph, GraphQL, Schemas, & CRUD – Ardan Labs

#11

Post by mrjn »

simonw wrote: post #8
mrjn wrote: post #6

Earlier quoted context omitted.

(author of Dgraph here) I'd argue relational DBs get way more credit than they're worth. And it is indeed tricky to make them work across different data models -- that's by now an established fact across big SV companies. Restricting direct access to rigid RDBMs and making data modeling easier via graphs is why Facebook Tao, Dropbox Edgestore, Airbnb Knowledge Graph and so on exist. See my post [1]. I'll give you a s…

> That's not simple, that's a big change which requires a bunch of work. I feel like many of these criticisms of RDBMS come from a perspective of not working with a great database migrations system. I've made changes like this (one-to-many switched for many-to-many) using Django migrations many times over, and I find it easy. But that's because I've built up the experience with the tooling over time. Learning migrati…

Hey Simon,

Totally see your perspective. You're already familiar with data migration, but not familiar with graph DBs. The former is just easier to do than to invest in the learning curve involved with the latter. Valid point.

My take is more root-cause and principle based. If we were to think of a different way to build a DB, then avoiding a data migration altogether is a better approach. Avoiding the downtime, extra work, extra code and so on is just better for the user. Moreover, simpler data models, avoiding data duplication and such become very convincing features.

It's also not so interesting to me when graph DBs are only applied to specific graph problems, like Page Rank and such. We didn't build Dgraph just to solve Page Rank. The reason we built Dgraph was because we saw the complex data modeling problem Google Knowledge Graph threw at us. Graph system allowed that problem to be solved in a really clean and simple way. And it's the same problem we see other companies dealing with as well.

Re: Dgraph, GraphQL, Schemas, & CRUD – Ardan Labs

#12

Post by mrjn »

default-kramer wrote: post #10
mrjn wrote: post #6

Earlier quoted context omitted.

(author of Dgraph here) I'd argue relational DBs get way more credit than they're worth. And it is indeed tricky to make them work across different data models -- that's by now an established fact across big SV companies. Restricting direct access to rigid RDBMs and making data modeling easier via graphs is why Facebook Tao, Dropbox Edgestore, Airbnb Knowledge Graph and so on exist. See my post [1]. I'll give you a s…

In your movie+director example, changing a relational database is relatively easy. Yes, you create two new tables but that is not hard. And you relocate the director data from the movie table into the new director table, also not hard. The hard part is updating all the application code that was written assuming that a movie has one director. I'm not super familiar with graph DBs, but I don't see how they could possib…

Add some producers, cinematographers, actors, oscar awards and so on. Complexity adds up.

OTOH, In Dgraph GraphQL, you'd just do a simple schema edit from:

type Movie { ... director: Director }

to

type Movie { ... directors: [Director] }

You're right about application code stuff. But, that's a common cost across both the spaces -- though, I'd argue that JSON responses back from GraphQL (/ Dgraph) make it easier.

Re: Dgraph, GraphQL, Schemas, & CRUD – Ardan Labs

#13

Post by mamcx »

mrjn wrote: post #6
mamcx wrote: post #5

>Relational databases are very rigid so you need to really make sure you understand your data upfront. Is NOT true: CREATE TABLE/VIEW ... ALTER TABLE ... SELECT (whatever) ... Changing a rdbms at runtime is fully supported, in MUCH better ways than almost all "nosql" databases. > Changing the database is a big effort Is much less effort than nosql. With more guaranties than the change is CORRECT, and not left you hal…

(author of Dgraph here) I'd argue relational DBs get way more credit than they're worth. And it is indeed tricky to make them work across different data models -- that's by now an established fact across big SV companies. Restricting direct access to rigid RDBMs and making data modeling easier via graphs is why Facebook Tao, Dropbox Edgestore, Airbnb Knowledge Graph and so on exist. See my post [1]. I'll give you a s…

> Later, if you realize that each movie can have multiple directors

This still require change across the codebase, where the db migration is fairly, the most simply step.

But:

Is similar to "static VS dynamic" where the change in rdbms come BEFORE the new data and in most nosql AFTER.

If somehow the data come in a "progressive do changes pls" then is clear the way most db schemas are, is harder with BEFORE.

So, yeah, exist places that a specialized store make more sense. But just say "is harder" invite this critique, and worse, in the minds of inexperience developers (that are the ones that deploy blind) could lead to "get out of a rdbms, are old and bad!", when in fact is much better, most of time.

ALSO:

> Restricting direct access to rigid RDBMs and making data modeling easier via graphs is why....

The relational model could handle that. BUT, the implementation inside rdbms is just a subset of the full potential. One example: You can't embed tables in tables.

And relational/sql engine have weak support for hierarchies and graph, despite the fact you see sql on top of other non-relational engines.

I'm building a relational lang in the spare time, and without the constrain of fit the(traditional) rdbms is clear the db guys need to up their game!

Re: Dgraph, GraphQL, Schemas, & CRUD – Ardan Labs

#14

Post by lmeyerov »

mrjn wrote: post #6
mamcx wrote: post #5

>Relational databases are very rigid so you need to really make sure you understand your data upfront. Is NOT true: CREATE TABLE/VIEW ... ALTER TABLE ... SELECT (whatever) ... Changing a rdbms at runtime is fully supported, in MUCH better ways than almost all "nosql" databases. > Changing the database is a big effort Is much less effort than nosql. With more guaranties than the change is CORRECT, and not left you hal…

(author of Dgraph here) I'd argue relational DBs get way more credit than they're worth. And it is indeed tricky to make them work across different data models -- that's by now an established fact across big SV companies. Restricting direct access to rigid RDBMs and making data modeling easier via graphs is why Facebook Tao, Dropbox Edgestore, Airbnb Knowledge Graph and so on exist. See my post [1]. I'll give you a s…

From a user perspective, what we find the graph dynamism is more important for Self-Serve Analytics, like a fast-moving data science or analyst or dev team, than for DBAs.

So a diff perspective:

DBA SCHEMA CHANGE - Relational: Admins alter the schema and devs maybe run a migration - Graph: Projects start untyped, but almost all Graphistry has helped are effectively & ultimately typed & locked. So ends up working same as relational. (Ex: ProjectDomino.org took just maybe 1mo before the neo4j DBA locked the schema to avoid inadvertent value pollution.)

DYNAMIC QUERIES Once a bunch of entity types and relationships get involved, you build up a zoo of tables. This is painful for adding data ("new dataset X needs schema Y, or subtypes into existing table Z by dynamic type field A + generic data stuffed into field metadata"), and much worse, given some data, trying to figure out how it indexes across 20+ tables. Three examples: an Infosec Jupyterthon talk was about how to make sense of OSQuery's ~100 different tables for OS logs, a genetics friend got onboarded to a DB with 30 tables & views they know nothing about, and in Project Domino, you can do all sorts of things with URLs and Topics across our datasets & analyses.

Relational is great for a rigid CRUD app. But once you hit analytics, you get swamped with data integration tasks (discovery, linking, fusion, ...), and tables become a PITA. Formally, graph queries like ("everything 1 step out") gives you genericity in quantification where SQL forces you to know the exact table name & field name ahead of time.

Re: Dgraph, GraphQL, Schemas, & CRUD – Ardan Labs

#15

Post by alexchamberlain »

mrjn wrote: post #12
default-kramer wrote: post #10

Earlier quoted context omitted.

In your movie+director example, changing a relational database is relatively easy. Yes, you create two new tables but that is not hard. And you relocate the director data from the movie table into the new director table, also not hard. The hard part is updating all the application code that was written assuming that a movie has one director. I'm not super familiar with graph DBs, but I don't see how they could possib…

Add some producers, cinematographers, actors, oscar awards and so on. Complexity adds up. OTOH, In Dgraph GraphQL, you'd just do a simple schema edit from: type Movie { ... director: Director } to type Movie { ... directors: [Director] } You're right about application code stuff. But, that's a common cost across both the spaces -- though, I'd argue that JSON responses back from GraphQL (/ Dgraph) make it easier.

I'm a massive proponent of the graph model, but the the RDBMS fans have it right here: the schema change is trivial in both cases; the hard part is managing the roll out of those changes to prevent outage on the application you are actually selling.

Re: Dgraph, GraphQL, Schemas, & CRUD – Ardan Labs

#16

Post by claytonjy »

vanilla-almond wrote: post #2

GraphQL seems to sit between the strict relational model and the more free-form approach of NoSQL databases (from I can see, but correct me if I am wrong). I have not used a GraphQL database, but one of the things I fear about designing a relational database is mentioned in the article: >"Relational databases are very rigid so you need to really make sure you understand your data upfront. Changing the database is a b…

It doesn't have to be, but tooling and initial design matters a lot. I've done a lot of significant migrations this year (changing schemas of hundreds of millions of rows in postgres) in a downtime-free, non-breaking way, but there were two big pieces:

- separate internal schemas from external ones, so you can change the internals while maintaining your interface contract. Your database has an API whether you realize it or not, so treat it like one. I literally have schemas like "api" and "api_v2".

- use a great migration tool. I've been using sqitch, which I love because it encourages me to think about how to _verify_ each migration does the correct thing. Tie that into CI/CD in a nice way and DB migrations are no longer scary

That probably downplays the effort; as someone who's never done DBA work before, I've had to learn a lot about PL/pgSQL, transaction isolation levels, role management, etc. for the first time. I think I'm better for it, though, and I've quite enjoyed going beyond query-writing.

Re: Dgraph, GraphQL, Schemas, & CRUD – Ardan Labs

#17

Post by tuatoru »

mrjn wrote: post #6
mamcx wrote: post #5

>Relational databases are very rigid so you need to really make sure you understand your data upfront. Is NOT true: CREATE TABLE/VIEW ... ALTER TABLE ... SELECT (whatever) ... Changing a rdbms at runtime is fully supported, in MUCH better ways than almost all "nosql" databases. > Changing the database is a big effort Is much less effort than nosql. With more guaranties than the change is CORRECT, and not left you hal…

(author of Dgraph here) I'd argue relational DBs get way more credit than they're worth. And it is indeed tricky to make them work across different data models -- that's by now an established fact across big SV companies. Restricting direct access to rigid RDBMs and making data modeling easier via graphs is why Facebook Tao, Dropbox Edgestore, Airbnb Knowledge Graph and so on exist. See my post [1]. I'll give you a s…

> I'll give you a simple example. Consider, movies and directors. If you started with the fact that each movie has exactly one director, you'd design exactly one table, with a director column.

With respect, if you have that little domain knowledge, you shouldn't be designing--er, coding--anything other than a throwaway exploratory scrap.

And in preference to doing that, you should be getting out and talking to the people who plan to use your database, and learning how they think, and what about.

Systems analysis is another '80s development "fad" that is way underrated.

Re: Dgraph, GraphQL, Schemas, & CRUD – Ardan Labs

#18

Post by xupybd »

tuatoru wrote: post #17
mrjn wrote: post #6

Earlier quoted context omitted.

(author of Dgraph here) I'd argue relational DBs get way more credit than they're worth. And it is indeed tricky to make them work across different data models -- that's by now an established fact across big SV companies. Restricting direct access to rigid RDBMs and making data modeling easier via graphs is why Facebook Tao, Dropbox Edgestore, Airbnb Knowledge Graph and so on exist. See my post [1]. I'll give you a s…

> I'll give you a simple example. Consider, movies and directors. If you started with the fact that each movie has exactly one director, you'd design exactly one table, with a director column. With respect, if you have that little domain knowledge, you shouldn't be designing--er, coding--anything other than a throwaway exploratory scrap. And in preference to doing that, you should be getting out and talking to the pe…

Businesses change very quickly. To say that you shouldn't code until you know the domain well enough to model it perfectly is not wise.

You build software to solve real world problems. Sometimes that means reworking the solution as the problem changes.

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