Graph data modeling suggestions¶

This section provides general suggestions for modeling data in Nebula Graph.

Model for performance¶

There is no perfect method to model in Nebula Graph. Graph modeling depends on the questions that you want to know from the data. Your data drives your graph model. Graph data modeling is intuitive and convenient. Create your data model based on your business model. Test your model and gradually optimize it to fit your business. To get better performance, you can change or re-design your model multiple times.

Design and evaluate the most important queries¶

Usually, various types of queries are validated in test scenarios to assess the overall capabilities of the system. However, in most production scenarios, there are not many types of frequently used queries. You can optimize the data model based on key queries selected according to the Pareto (80/20) principle.

No predefined bonds between Tags and Edge types¶

Define the bonds between Tags and Edge types in the application, not Nebula Graph. There are no statements that could get the bonds between Tags and Edge types.

Tags/Edge types predefine a set of properties¶

While creating Tags or Edge types, you need to define a set of properties. Properties are part of the Nebula Graph Schema.

Control changes in the business model and the data model¶

Some graph databases are designed to be Schema-free, so their data modeling, including the modeling of the graph topology and properties, can be very flexible. Properties can be re-modeled to graph topology, and vice versa. Such systems are often specifically optimized for graph topology access.

Nebula Graph 2.5.1 is a strong-Schema (row storage) system, which means that the business model should not change frequently. For example, the property Schema should not change. It is similar to avoiding ALTER TABLE in MySQL.

On the contrary, vertices and their edges can be added or deleted at low costs. Thus, the easy-to-change part of the business model should be transformed to vertices or edges, rather than properties.

For example, in a business model, people have relatively fixed properties such as age, gender, and name. But their contact, place of visit, trade account, and login device are often changing. The former is suitable for modeling as properties and the latter as vertices or edges.

Breadth-first traversal over depth-first traversal¶

Nebula Graph has lower performance for depth-first traversal based on the Graph topology, and better performance for breadth-first traversal and obtaining properties. For example, if model A contains properties "name", "age", and "eye color", it is recommended to create a Tag person and add properties name, age, and eye_color to it. If you create a Tag eye_color and an Edge type has, and then create an edge to represent the eye color owned by the person, the traversal performance will not be high.

The performance of finding an edge by an edge property is close to that of finding a vertex by a vertex property. For some databases, it is recommended to re-model edge properties as those of the intermediate vertices. For example, model the pattern (src)-[edge {P1, P2}]->(dst) as (src)-[edge1]->(i_node {P1, P2})-[edge2]->(dst). With Nebula Graph 2.5.1, you can use (src)-[edge {P1, P2}]->(dst) directly to decrease the depth of the traversal and increase the performance.

Edge directions¶

To query in the opposite direction of an edge, use the syntax (dst)<-[edge]-(src) or GO FROM dst REVERSELY.

If you don't care about the directions or want to query against both directions, use the syntax (src)-[edge]-(dst) or GO FROM src BIDIRECT.

Therefore, there is no need to insert the same edge redundantly in the reversed direction.

Set Tag properties appropriately¶

Put a group of properties that are on the same level into the same Tag. Different groups represent different concepts.

Use indexes correctly¶

Using property indexes helps find VIDs through properties, but can lead to performance decrease by 90% or even more. Only use an index when you need to find vertices or edges through their properties.

Design VIDs appropriately¶

See VID.

Long texts¶

Do not use long texts to create edge properties. Edge properties are stored twice and long texts lead to greater write amplification. For how edges properties are stored, see Storage architecture. It is recommended to store long texts in HBase or Elasticsearch and store its address in Nehula Graph.

Dynamic graphs (sequence graphs) are not supported¶

In some scenarios, graphs need to have time information to describe how the structure of the entire graph changes over time.¹

The Rank field on Edges in Nebula Graph 2.5.1 can be used to store time in int64, but no field on vertices can do this because if you store the time information as property values, it will be covered by new insertion. Thus Nebula Graph does not support sequence graphs.