Software Alternatives, Accelerators & Startups

Graphweaver VS socketify.py

Compare Graphweaver VS socketify.py and see what are their differences

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Graphweaver logo Graphweaver

Turn multiple data sources into a single GraphQL API

socketify.py logo socketify.py

Maybe the fastest web framework for Python and PyPy
  • Graphweaver Landing page
    Landing page //
    2023-08-23

Graphweaver is a GraphQL Gateway that can connect many data sources together to create an API. It can be used to create a headless CMS, an API Gateway, or used as a Backend for mobile apps.

Why?

We consistently find that everyone has lots of sources of truth. You know, CRM holding customer data, accounting systems handling invoices, and more scattered across different SaaS platforms and databases? It's a real pain to sync it all up!

In the past we used to copy data from everywhere to the DB, but that always breaks at some point.

Well, after years of grappling with this issue, we wanted a way to easily build a single GraphQL API in front of all those sources. An API that allows you to execute queries that even span across datasources (give me DB records where customer in CRM name is "Bob"), and also allows you to administer your data all from one place.

That's why we built Graphweaver. We've been using it on our projects for about a year now and think you'll love it too!

Features

๐Ÿ“ Code-first GraphQL API: Save time and code efficiently with our code-first approach. ๐Ÿš€ Built for Node in Typescript: The power of Typescript combined with the flexibility of Node.js. ๐Ÿ”— Connect to Multiple Datasources: Seamlessly integrate Postgres, MySql, Sqlite, REST, and more. ๐ŸŽฏ Instant GraphQL API: Get your API up and running quickly with automatic queries and mutations. ๐Ÿ”„ One Command Import: Easily import an existing database with a simple command-line tool.

  • socketify.py Landing page
    Landing page //
    2023-09-24

Graphweaver features and specs

  • Integration
    Graphweaver allows for the integration of multiple data sources, providing a unified view and ease of data management.
  • Efficiency
    It enhances the efficiency of data retrieval by using GraphQL, which minimizes data over-fetching.
  • Flexibility
    Graphweaver supports flexible query structures, which can be tailored to specific data needs and requirements.
  • Developer Experience
    Provides a developer-friendly experience with comprehensive documentation and tools to streamline the development process.

Possible disadvantages of Graphweaver

  • Complexity
    The initial setup and configuration can be complex, especially for developers who are not familiar with GraphQL or integrating diverse data sources.
  • Learning Curve
    There might be a steep learning curve for new users who are not accustomed to using GraphQL or related technologies.
  • Resource Intensive
    Integrating many data sources might demand higher computational resources, which could increase operational costs.

socketify.py features and specs

  • High Performance
    Socketify.py is designed for high scalability and performance, leveraging an efficient event loop and native extensions to handle a large number of concurrent connections efficiently.
  • WebSocket Support
    The library provides built-in support for WebSockets, making it suitable for real-time applications where persistent connections between client and server are necessary.
  • Asynchronous I/O
    Socketify.py is built on top of asynchronous I/O paradigms, allowing non-blocking operations that can improve the throughput of networked applications.
  • Ease of Use
    The library offers a clean and straightforward API with examples and documentation, which lowers the barrier to entry for developers who are new to network programming in Python.
  • Python Integration
    Being a Python library, socketify.py integrates well with existing Python applications and can be included as part of larger, multi-component systems.

Possible disadvantages of socketify.py

  • Limited Adoption
    As a relatively new or niche library, socketify.py might have a smaller user base and community compared to more established frameworks like Flask or Django, which could result in fewer community resources and third-party integrations.
  • Learning Curve
    For developers who are accustomed to synchronous programming paradigms, adapting to the asynchronous programming model of socketify.py may require an initial learning investment.
  • Documentation Depth
    While there is documentation, it might not be as extensive or comprehensive as those of more mature libraries, potentially requiring more experimentation or source code reading to fully grasp advanced features.
  • Potential Stability Issues
    Being less established, there might be undiscovered bugs or stability issues in production environments compared to long-standing Python networking libraries.
  • Ecosystem Limitations
    The library might lack some of the extensive third-party plugins or tools available in more popular frameworks, which could limit its extensibility.

Analysis of socketify.py

Overall verdict

  • Socketify.py is a solid choice for developers seeking a high-performance web framework in Python, particularly for I/O-bound applications requiring speed comparable to frameworks in compiled languages, thanks to its use of uWebSockets under the hood.

Why this product is good

  • Built on uWebSockets, providing significant performance improvements over traditional Python web frameworks
  • Supports WebSockets natively, making it suitable for real-time applications
  • Lightweight and minimalistic design reduces overhead
  • Compatible with ASGI, allowing integration with existing Python async ecosystem
  • Active development and growing community support on GitHub
  • Good for building high-throughput APIs and services

Recommended for

  • Developers building real-time applications like chat apps or live notifications
  • Projects requiring high concurrency and low latency in Python
  • Teams looking to replace slower WSGI-based frameworks with something faster
  • Applications needing WebSocket support without heavy framework overhead
  • Microservices architectures where performance is critical
  • Python developers wanting an alternative to Node.js for performance-sensitive tasks

Graphweaver videos

Graphweaver live demo at the Atlassian head-office for SydJS

More videos:

  • Demo - Quick Start

socketify.py videos

No socketify.py videos yet. You could help us improve this page by suggesting one.

Add video

Category Popularity

0-100% (relative to Graphweaver and socketify.py)
GraphQL
100 100%
0% 0
Web Development
0 0%
100% 100
API-first CMS
100 100%
0% 0
Websocket
0 0%
100% 100

User comments

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Social recommendations and mentions

Based on our record, socketify.py should be more popular than Graphweaver. It has been mentiond 2 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Graphweaver mentions (1)

  • Getting started creating a web app with multiple data sources? Graphweaver!
    Weโ€™re a small dev team based in Sydney and in between client projects weโ€™ve been working on our own open-source tool, Graphweaver. Graphweaver allows you to combine multiple data sources (Databases, Rest APIs, Saas platforms) and expose a single GraphQL API. Itโ€™s a bit like Hasura or Step Zen but with more of a code-first flexibility. It can take your database and with a single import command, generate your code... Source: almost 3 years ago

socketify.py mentions (2)

  • Show HN: Python framework is faster than Golang Fiber
    These "benchmarks" are useless, they're not testing anything real world except the performance of uWebsockets. There are copy errors all over the place. And then an advertisement: https://github.com/cirospaciari/socketify.py#briefcase-comme... Is this a professional framework that produces proper, real-world benchmarks and... - Source: Hacker News / over 3 years ago
  • This is how I started the development of the fastest ASGI and WSGI Server in TechEmPower Benchmarks
    After starting the project called socketify.py at https://github.com/cirospaciari/socketify.py, I got pretty good results and reviews, but many people asked if socketify.py could be used to create a WSGI and ASGI server. WSGI and ASGI have a lot of overhead, that's is why I choose not to use them in the first place, but adding an ASGI and WSGI server allows a lot of code already written to run faster! Source: over 3 years ago

What are some alternatives?

When comparing Graphweaver and socketify.py, you can also consider the following products

Hasura - Hasura is an open platform to build scalable app backends, offering a built-in database, search, user-management and more.

GraphQL - GraphQL is a data query language and runtime to request and deliver data to mobile and web apps.

GraphQL Hive - Open Source GraphQL Federation Platform

FastAPI - FastAPI is an Open Source, modern, fast (high-performance), web framework for building APIs with Python 3.6+ based on standard Python type hints.

Grafbase - Unify the data layer with GraphQL

PostgREST - Automatic REST API for Any Postgres Database