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Yes, you're wrong. You're wrong because you need to JOIN a massive tree of blocks, to form the graph the author is referring to. You can break out the "block"

Yes, you're wrong. You're wrong because you need to JOIN a massive tree of blocks, to form the graph the author is referring to. You can break out the "block" model into several tables and represent it in a relational database that way. NoSQL = NO JOIN? Hope that helps.

jitl 5y ago
We don't use JOIN for the content tree; I don't think I've seen one in any of our queries.
- RyanGoosling 5y ago
  What do your queries look like? Are you using an ORM?
  - jitl 5y ago
    We don't use an ORM. Notion's codebase on the back-end is much more functional than object-oriented, in the sense that we have many more code that looks like `transformTheData(theData, theChangeToMake): ResultingData` than we have classes or methods. We do lean very heavily on the TypeScript type system and try to make invalid states unrepresentable.
    - bionhoward 5y ago
      have you tried "data last" FP like `transformTheData(theChangeToMake, theData): ResultingData` instead? I learned this from Ramda.JS, makes it way easier to leverage currying, ex `change = transformTheData(theChangeToMake); change(theData)`
setr 5y ago
I don’t actually see a graph represented anywhere in the article; the author references wanting a graph at the start, but the only thing I’m seeing described are trees of nested blocks. Even the properties list seems to be a grab-bag of KV pairs that gets permanently attached to a block once initialized, to support roundtripping Which is pretty much the ideal scenario for a document store. The article describes Notion as being very strictly hierarchal
- RyanGoosling 5y ago
  A block has many properties. A property has a name, and a value. The underlying persisted data doesn't necessarily have to be a bag of KV pairs. A block is related to its parent and descendant blocks. These relations are suitably represented in a relational database, not a document store. EDIT: In graph theory, a tree is an undirected, connected and acyclic graph.
  - setr 5y ago
    A document store is basically optimized for specifically hierarchal data situations — a tree. The data structure you’re describing, and what the article describes, is precisely that: a tree. When comparing a document store versus a RDBMS, in terms of suitability and appropriateness, the distinction is primarily along the lines of a tree, versus an arbitrary graph (by which I mean that an RDBMS is more powerful, and more general, but not inherently as optimal in either performance, “scalability”, or UX in the places where a document store makes sense. More specifically, the way the article describes it, you’re not interested in “give me every block of type X” — you’re only interested in “given block Y, what type is it?”. That is, the question is one-way, and fits cleanly in a hierarchal format of a document store. The only question posed that operates in the reverse direction is permissions, though even that’s a little odd, since it seems to me it should only go “downwards” as well — a block’s permission scope is the sum of all of its parents, and you can store it there upon iteration. > The underlying persisted data doesn't necessarily have to be a bag of KV pairs. It doesn’t have to be... but it can be, and appears to be. > A block is related to its parent and descendant blocks. Right; the singular parent, and the multiple children. A tree. > In graph theory, a tree is an undirected, connected and acyclic graph. When discussing trees and graphs, I think it’s obvious a distinction is being made between a graph forming a tree, and graph forming a not-tree (more complex than a tree). When I say that a square is easier to encode than a rectangle, I do not mean that a square is not a rectangle, but that a rectangle is not a square — that a square’s more specific properties give us opportunity to simplify/optimize (I only need to store one length to represent it). A database can encode a tree just fine, but that doesn’t mean it’s the best tool to do so. There are other properties to a document store I don’t care for, and I don’t like them in general (like the implicit schema, and total lack of data consistency validation by the data store, and the fact that you often don’t truly have a tree), but representing a tree is what’s been described, and it’s exactly what they’re specialized for. If you want to argue against it, you need to specify why you think this isn’t a tree, because I feel it’s quite obvious it is.
ellimilial 5y ago
@setr explained it really well. A side note, NoSQL also includes graph databases, dedicated to this type of node/relationship traversal.

jitl 5y ago

We don't use JOIN for the content tree; I don't think I've seen one in any of our queries.

RyanGoosling 5y ago
What do your queries look like? Are you using an ORM?
- jitl 5y ago
  We don't use an ORM. Notion's codebase on the back-end is much more functional than object-oriented, in the sense that we have many more code that looks like `transformTheData(theData, theChangeToMake): ResultingData` than we have classes or methods. We do lean very heavily on the TypeScript type system and try to make invalid states unrepresentable.
  - bionhoward 5y ago
    have you tried "data last" FP like `transformTheData(theChangeToMake, theData): ResultingData` instead? I learned this from Ramda.JS, makes it way easier to leverage currying, ex `change = transformTheData(theChangeToMake); change(theData)`

setr 5y ago

I don’t actually see a graph represented anywhere in the article; the author references wanting a graph at the start, but the only thing I’m seeing described are trees of nested blocks. Even the properties list seems to be a grab-bag of KV pairs that gets permanently attached to a block once initialized, to support roundtripping Which is pretty much the ideal scenario for a document store. The article describes Notion as being very strictly hierarchal

RyanGoosling 5y ago
A block has many properties. A property has a name, and a value. The underlying persisted data doesn't necessarily have to be a bag of KV pairs. A block is related to its parent and descendant blocks. These relations are suitably represented in a relational database, not a document store. EDIT: In graph theory, a tree is an undirected, connected and acyclic graph.
- setr 5y ago
  A document store is basically optimized for specifically hierarchal data situations — a tree. The data structure you’re describing, and what the article describes, is precisely that: a tree. When comparing a document store versus a RDBMS, in terms of suitability and appropriateness, the distinction is primarily along the lines of a tree, versus an arbitrary graph (by which I mean that an RDBMS is more powerful, and more general, but not inherently as optimal in either performance, “scalability”, or UX in the places where a document store makes sense. More specifically, the way the article describes it, you’re not interested in “give me every block of type X” — you’re only interested in “given block Y, what type is it?”. That is, the question is one-way, and fits cleanly in a hierarchal format of a document store. The only question posed that operates in the reverse direction is permissions, though even that’s a little odd, since it seems to me it should only go “downwards” as well — a block’s permission scope is the sum of all of its parents, and you can store it there upon iteration. > The underlying persisted data doesn't necessarily have to be a bag of KV pairs. It doesn’t have to be... but it can be, and appears to be. > A block is related to its parent and descendant blocks. Right; the singular parent, and the multiple children. A tree. > In graph theory, a tree is an undirected, connected and acyclic graph. When discussing trees and graphs, I think it’s obvious a distinction is being made between a graph forming a tree, and graph forming a not-tree (more complex than a tree). When I say that a square is easier to encode than a rectangle, I do not mean that a square is not a rectangle, but that a rectangle is not a square — that a square’s more specific properties give us opportunity to simplify/optimize (I only need to store one length to represent it). A database can encode a tree just fine, but that doesn’t mean it’s the best tool to do so. There are other properties to a document store I don’t care for, and I don’t like them in general (like the implicit schema, and total lack of data consistency validation by the data store, and the fact that you often don’t truly have a tree), but representing a tree is what’s been described, and it’s exactly what they’re specialized for. If you want to argue against it, you need to specify why you think this isn’t a tree, because I feel it’s quite obvious it is.

ellimilial 5y ago

@setr explained it really well. A side note, NoSQL also includes graph databases, dedicated to this type of node/relationship traversal.