Software Alternatives, Accelerators & Startups
Register | Login

RisingWave VS socketify.py

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

Umso
The Website Builder for Startups featured
Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.
Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

RisingWave logo RisingWave

RisingWave is a stream processing platform that utilizes SQL to enhance data analysis, offering improved insights on real-time data.

socketify.py logo socketify.py

Maybe the fastest web framework for Python and PyPy
  • RisingWave Landing page
    Landing page //
    2023-08-29
  • socketify.py Landing page
    Landing page //
    2023-09-24

RisingWave features and specs

No features have been listed yet.

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

RisingWave videos

+ Add

RisingWave: Reinventing(?!) Stream Processing in the Cloud Era (Yingjun Wu)

More videos:

  • Review - Building Cost Effective Stream Processing Applications with RisingWave and Pulsar
  • Review - RISINGWAVE REBOOT

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 RisingWave and socketify.py)

RisingWave

socketify.py

Databases
100 100%
Databases
0% 0
Python
0 0%
Python
100% 100
Stream Processing
100 100%
Stream Processing
0% 0
Websocket
0 0%
Websocket
100% 100

User comments

Share your experience with using RisingWave and socketify.py. For example, how are they different and which one is better?
Log in or Post with

Social recommendations and mentions

Based on our record, RisingWave should be more popular than socketify.py. It has been mentiond 18 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.

RisingWave mentions (18)

  • Build a Real-Time Gaming Analytics Pipeline with Justย SQL
    Player data is ingested into a Kafka topic, and RisingWave consumes this stream to create materialized views for real-time analysis. Using BI tools like Superset or Grafana, weโ€™ll build dashboards to monitor player performance and power leaderboards. Finally, Iโ€™ll show how the results from RisingWave can be sent to analytics platforms like BigQuery, Snowflake, or StarRocks and ML models for downstream applications... - Source: dev.to / 11 months ago
  • The Equality Delete Problem in Apache Iceberg
    RisingWave is the only system today that supports complete, end-to-end architecture for streaming CDC into Apache Iceberg, making it the state-of-the-art solution in this space. - Source: dev.to / 12 months ago
  • Towards Sub-100ms Latency Stream Processing with an S3-Based Architecture
    RisingWave is a high-performance streaming database built in Rust. Itโ€™s PostgreSQL-compatible and lets users write sophisticated stream processing logic using standard SQL - no need to learn a new DSL or framework. - Source: dev.to / about 1 year ago
  • Unlock the Power of Realโ€‘Time HubSpot CRM Automation
    We're excited to announce that now you can: by integrating HubSpot webhooks directly with RisingWave. This powerful connection allows you to stream your CRM, marketing, and sales data from HubSpot into our unified data platform for true real-time processing, analysis, and automation. - Source: dev.to / about 1 year ago
  • Introducing RisingWave's Hosted Iceberg Catalog-No External Setup Needed
    At RisingWave, our goal is to simplify the process of building real-time data applications. A key part of this is enabling users to build modern, open data architectures. Thatโ€™s why we developed the Iceberg Table Engine (see the Iceberg table engine docs), which allows you to stream data directly into tables using the open Apache Iceberg format. This is a powerful way to build a streaming lakehouse where your data... - Source: dev.to / about 1 year ago
View more

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 RisingWave and socketify.py, you can also consider the following products

Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.

Materialize - A Streaming Database for Real-Time Applications

Apache Kafka - Apache Kafka is an open-source message broker project developed by the Apache Software Foundation written in Scala.

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

Timeplus - An innovative streaming SQL database and real-time analytics platform. Fast, powerful and intuitive

ClickHouse - ClickHouse is an open-source column-oriented database management system that allows generating analytical data reports in real time.

Loading...