Note_Tech

All technological notes.

---

Project maintained by simonangel-fong Hosted on GitHub Pages — Theme by mattgraham

Neo4j - GraphDB

Back

• Neo4j - GraphDB
  • GraphDB
    • Labeled Property Graph Model
  • Pros and Cons
  • Graph Database vs. RDBMS
  • GraphDB vs NoSQL Database

---

GraphDB

• graph

  • a collection of vertices and edges
  • a set of nodes and the relationships that connect them

• Graph database

  • very useful now a day because in graph databases data exist in the form of the relationship between different objects.
  • The relationship between the data is more valuable than the data itself.
  • can be used with OLTP systems
    • provide features like transactional integrity and operational availability.

---

Labeled Property Graph Model

• Nodes

  • represent entities and complex types
  • can contain properties (key-value pairs).
  • Each node can have different properties

• Relationships

  • Every relationship has a name and direction
  • Relationships can contain properties, which can further clarify the relationship
  • Must have a start and end node

• Properties

  • Key value pairs used for nodes and relationships
  • Adds metadata to your nodes and relationships
  • Entity attributes
  • Relationship qualities

• Labels

  • Used to represent objects in your domain (e.g. user, person, movie)
  • With labels, you can group nodes
  • Allows us to create indexes and constraints with groups of nodes

---

Pros and Cons

• Pros:
  • Powerful data model, as general as RDBMS
  • Connected data locally indexed
  • Easy to query
• Cons
  • Sharding (lots of people working on this)
    • Scales UP reasonably well
  • Requires rewiring your brain

---

Graph Database vs. RDBMS

Graph Database	RDBMS
data is stored in graphs.	data is stored in tables.
there are nodes	there are rows
there are properties and their values.	there are columns and data.
the connected nodes are defined by relationships	constraints are used instead of that.
traversal is used instead of join.	join is used instead of traversal.

• Vs Relational databases

  • Relational databases store highly structured data which have several records storing the same type of data
    • so they can be used to store structured data
    • they do not store the relationships between the data
  • graph databases store relationships and connections as first-class entities.
• Join tables => relationships
• columns => relationship properties

---

GraphDB vs NoSQL Database

• NoSQL databases

  • store sets of disconnected aggregates, making it difficult to use them for connected data and graphs.
  • Relational database: It is represented in tabular form so it is best for calculating the income.
  • Key-Value Store: It is best for building a shopping cart.
  • NoSQL databases: It is stored as a document so, it is best for storing structured product information.
  • GraphDB: It follows a graph structure. It is best for describing how a user got from point A to point B.

• Types:

  • Document Stores
    • Binary Large Objects (BLOBs)
    • MongoDB
  • Key-Value Stores
    • no joins and aggregate functions
    • Amazon DynamoDB and Apache Cassandra
  • Columnar Databases
    • Every row can have its own schema
    • HBase
  • Graph Databases
    • vertices and edges.
    • Neo4j