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PostgREST

60
119
+ 1
8
pREST

10
24
+ 1
0
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PostgREST vs pREST: What are the differences?

  1. Authentication and Authorization: One key difference between PostgREST and pREST is their approach to authentication and authorization. PostgREST uses JWT (JSON Web Tokens) for authentication and has built-in support for role-based access control (RBAC). On the other hand, pREST does not have built-in support for authentication and authorization, requiring additional setup and configuration.

  2. API Generation: Another difference is how the APIs are generated. PostgREST automatically generates RESTful APIs from an existing PostgreSQL database, providing a CRUD interface for the tables and views. pREST, on the other hand, requires manual definition of the API endpoints in a TOML file, making it more customizable but also requiring more effort for initial setup.

  3. Configuration and Customization: PostgREST is relatively easy to set up and requires minimal configuration, as it generates APIs based on the database schema. It also provides limited customization options, making it suitable for simple use cases. In contrast, pREST offers more configuration options, allowing for greater flexibility in defining API behavior and customizing the endpoints. This makes pREST a better choice for complex use cases that require fine-grained control over API behavior.

  4. Performance: When it comes to performance, PostgREST has been optimized for handling large amounts of data and high concurrency. It utilizes database prepared statements and connection pooling to improve performance. On the other hand, pREST may not have the same level of optimization and scalability as PostgREST, potentially leading to performance issues when dealing with large datasets or high traffic.

  5. Ecosystem and Community: While both PostgREST and pREST have active communities, PostgREST has a larger ecosystem and community support. It has been around for a longer time, has more contributors, and offers extensive documentation and examples. This larger ecosystem can be beneficial for developers who are looking for resources, support, and solutions to common problems.

  6. Maturity and Stability: PostgREST is considered more mature and stable compared to pREST. It has been widely adopted in production environments and is known for its reliability. In contrast, pREST is relatively newer and may still be undergoing development and improvements. This difference in maturity and stability should be considered when choosing between the two frameworks for a production application.

In Summary, PostgREST offers built-in authentication and authorization, automatic API generation from a PostgreSQL database, and has a larger ecosystem and community support. On the other hand, pREST provides more configuration options and customization possibilities, making it suitable for complex use cases. Developers should also consider the difference in performance, maturity, and stability when deciding between the two frameworks.

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Pros of PostgREST
Pros of pREST
  • 4
    Fast, simple, powerful REST APIs from vanilla Postgres
  • 2
    JWT authentication
  • 1
    Very fast
  • 1
    Declarative role based security at the data layer
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    What is PostgREST?

    PostgREST serves a fully RESTful API from any existing PostgreSQL database. It provides a cleaner, more standards-compliant, faster API than you are likely to write from scratch.

    What is pREST?

    Serve a RESTful API from any PostgreSQL database. There is the PostgREST written in haskell, keep a haskell software in production is not easy job, with this need that was born the pREST.

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    What companies use PostgREST?
    What companies use pREST?
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    What tools integrate with PostgREST?
    What tools integrate with pREST?
    What are some alternatives to PostgREST and pREST?
    GraphQL
    GraphQL is a data query language and runtime designed and used at Facebook to request and deliver data to mobile and web apps since 2012.
    MySQL
    The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
    PostgreSQL
    PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.
    MongoDB
    MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
    Redis
    Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.
    See all alternatives