EdgeDB vs PostgreSQL: What are the differences?

Introduction

This Markdown code provides a comparison between EdgeDB and PostgreSQL, highlighting their key differences. The differences between the two database systems are discussed in the following paragraphs.

1. Data Modeling Approach: EdgeDB utilizes a more advanced object-relational data modeling approach compared to PostgreSQL. While PostgreSQL follows a traditional relational model, EdgeDB introduces object-oriented concepts such as entities, links, and properties, allowing for more flexible and expressive data modeling capabilities.

2. Query Language: PostgreSQL employs SQL (Structured Query Language) as its primary query language, which is widely adopted and standardized. On the other hand, EdgeDB introduces its own query language, called EdgeQL, which is specifically designed to work seamlessly with its enhanced data modeling capabilities. EdgeQL offers powerful features, such as set expressions and graph traversal, making it more suitable for complex querying requirements.

3. Type System: PostgreSQL has a rich and extensive type system, supporting various data types, including built-in and user-defined types. EdgeDB further extends PostgreSQL's type system by introducing additional scalar types like UUID and DateTimeTZ. Additionally, EdgeDB introduces object types, allowing users to define complex data structures and relationships that go beyond PostgreSQL's traditional column-based approach.

4. Consistency Guarantees: PostgreSQL provides Acid-compliant transactions, ensuring consistency, isolation, durability, and atomicity. In contrast, EdgeDB takes consistency guarantees to a higher level by adopting a strongly consistent model. It ensures transactions are serialized, enforcing strict consistency at all times, even in distributed scenarios. This allows for precise control over data integrity and correctness.

5. Versioning and Time Travel: EdgeDB incorporates versioning and time travel as inherent features, enabling efficient management of historical data. It automatically tracks and records changes to data, allowing easy retrieval of past states and effective auditing. PostgreSQL, although capable of managing historical data using triggers or additional techniques, lacks native support for versioning and time travel.

6. Schema Evolution: In PostgreSQL, modifying database schema often involves complex operations and manual interventions, such as altering tables or rewriting data. EdgeDB, on the other hand, comes with a built-in schema management system that simplifies schema evolution. It allows for seamless modifications to the schema, such as adding new types, altering existing ones, or creating new relationships, without the need for extensive manual intervention or impacting existing data.

In summary, EdgeDB differentiates itself from PostgreSQL by employing an advanced object-relational data modeling approach, introducing its own query language, offering an extended type system, providing stronger consistency guarantees, incorporating versioning and time travel as native features, and simplifying schema evolution with its built-in schema management system.