Meltano VS FastAPI

Compare Meltano VS FastAPI and see what are their differences

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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.

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2023-08-04

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2023-05-14

Meltano

Website: meltano.com
$ Details

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FastAPI

Website: fastapi.tiangolo.com
$ Details: free
Startup details
Country: Colombia

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Meltano features and specs

Open Source
Meltano is open-source, which means that it is free to use and can be customized according to specific business needs. The open-source nature fosters a community-driven approach to improvements and updates.
Modular Architecture
Meltano offers a modular architecture that allows users to mix and match different components like extractors, loaders, and transformers, providing flexibility and adaptability.
Integration with Singer Taps
It is compatible with Singer Taps and Targets, enabling Meltano to connect with a wide variety of data sources and destinations, making data integration seamless.
Command Line Interface (CLI)
Meltano provides a robust CLI that simplifies managing and orchestrating ETL workflows, which can be advantageous for developers who prefer working with command-line tools.
Community and Support
There is a vibrant community and an active support system, which can be helpful for troubleshooting and getting advice on best practices regarding Meltano usage.

Possible disadvantages of Meltano

Steep Learning Curve
For users who are not familiar with command line tools or open-source data integration platforms, Meltano can have a steep learning curve, requiring time and effort to master.
Limited Built-in Features
While being modular offers flexibility, Meltano has fewer built-in features compared to some commercial ETL tools, which might require users to build custom solutions.
Variable Support for Sources/Destinations
The quality and reliability of connectors can vary since Meltano relies on community-contributed Singer Taps, which may not be as stable or well-documented as proprietary alternatives.
Complex Configuration
Initial setup and configuration can be complex, especially when connecting to multiple data sources or when customization is necessary, which may require significant technical expertise.
Resource Dependency
As an evolving open-source project, Meltano may require more resources in terms of time and effort to stay updated with the latest features and community contributions.

FastAPI features and specs

High Performance
Built on Starlette and Pydantic, FastAPI is one of the fastest frameworks for Python, providing high performance due to its asynchronous request handling.
Automatic Interactive API Documentation
FastAPI automatically generates interactive API documentation via Swagger UI and ReDoc, which are very helpful for development and testing.
Type Checking and Validation
With Pydantic models and Python type hints, FastAPI provides automatic data validation and type checking, reducing the chance of runtime errors.
Ease of Use
Its syntax and design make it easy to learn for Python developers, offering a smooth development experience while reducing boilerplate code.
Asynchronous Support
FastAPI supports asynchronous programming, allowing for better performance for I/O-bound operations, making it optimal for handling many simultaneous connections.
Extensive Documentation
It has comprehensive and well-structured documentation, which is very useful for both beginners and advanced users.
Community and Ecosystem
FastAPI has a growing community and ecosystem, with many plugins and integrations available to extend its functionality.

Possible disadvantages of FastAPI

Learning Curve for Asynchronous Programming
Although FastAPI itself is easy to learn, grasping the concepts of asynchronous programming in Python can be challenging for beginners.
Complex Dependencies
Using Pydantic for advanced validation can make the request models complex, requiring a deeper understanding of Pydantic and its functionalities.
Early Stage Libraries
Some third-party libraries and extensions specifically tailored for FastAPI might still be in early stages of development and lack long-term stability.
Limited Real-World Examples
Although the documentation is extensive, there might be limited real-world examples and case studies readily available compared to more mature frameworks.
Deployment Complexity
Deploying FastAPI applications might be more complex in comparison to traditional synchronous frameworks, mainly due to the need for asynchronous server setups.

Analysis of FastAPI

Overall verdict

FastAPI is widely regarded as a good choice, especially for applications that require high performance, scalability, and modern Python features. It is suitable for both simple and complex projects, making it a versatile tool in the web development ecosystem.

Why this product is good

FastAPI is a modern, fast (high-performance), web framework for building APIs with Python 3.7+ based on standard Python type hints. It is built on top of Starlette for web framework capabilities and Pydantic for data validation and settings management. FastAPI is known for its excellent performance, automatic generation of interactive API documentation (with Swagger and Redoc), and support for asynchronous programming. Developers appreciate its ease of use, detailed documentation, and helpful error messages.

Recommended for

Developers building RESTful APIs
Teams looking for a high-performance ASGI-based web framework
Projects that require asynchronous programming capabilities
Applications needing automatic generation of interactive API documentation
Python developers who prefer utilizing type hints for code clarity and validation

Meltano videos

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Meltano tutorial

FastAPI videos

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FastAPI from the ground up

Category Popularity

0-100% (relative to Meltano and FastAPI)

FastAPI

Developer Tools

9 9%

Developer Tools

91% 91

Data Dashboard

100 100%

Data Dashboard

0% 0

API Tools

0 0%

API Tools

100% 100

Business Intelligence

100 100%

Business Intelligence

0% 0

User comments

Share your experience with using Meltano and FastAPI. For example, how are they different and which one is better?

Reviews

These are some of the external sources and on-site user reviews we've used to compare Meltano and FastAPI

Meltano Reviews

Top 11 Fivetran Alternatives for 2024

Meltano was established in 2018 as an open-source project within GitLab to assist their data and analytics team. It’s a Python framework based on the Singer protocol. Originally developed by the founders of Stitch, the Singer framework saw reduced contributions after Stitch was acquired by Talend, which was later acquired by Qlik. Despite these changes, Meltano has continued...

Source: estuary.dev

Top 10 Fivetran Alternatives - Listing the best ETL tools

The platform provides users with a wide range of integration options, including connectors for databases, APIs, and application logs. Additionally, Meltano provides extensive support for data transformation and orchestration and integrates well with several cloud-based data warehouses.

Source: weld.app

FastAPI Reviews

Kurslog team

· Working at Kurslog · 4 months ago

When our backend team needs to build services for data parsing, aggregators, or high-load APIs, FastAPI is our absolute go-to choice. It completely lives up to its name-development speed is outstanding.

The combination of Pydantic for data validation and built-in async support keeps our shared codebase clean, strictly typed, and reliable. But the biggest highlight for our cross-functional team is the automatic generation of interactive OpenAPI (Swagger) documentation. Our frontend and mobile developers no longer have to wait for backend engineers to manually update API docs; everything stays perfectly in sync automatically. It has drastically improved our team's communication and delivery speed.

🏁 Competitors: Django, Flask, ExpressJS, Nest.js, Spring Boot

👍 Pros: Blazing fast performance (on par with nodejs and go)|Native asynchronous support out of the box|Automatic, interactive documentation generation (swagger/redoc)|Strict typing and data validation with pydantic

👎 Cons: Smaller plug-and-play ecosystem compared to older frameworks like django|Requires our architects to design the project structure and directory layout from scratch

The 20 Best Laravel Alternatives for Web Development

FastAPI, as the name hints, is a swift mover. Built on Starlette, it’s all about speed and performance with Python. Crafting API masterpieces at the speed of light, now that’s something.

Source: tms-outsource.com

25 Python Frameworks to Master

Since its release in 2018, it has rapidly gained popularity due to its great performance and simplicity. In fact, according to PyPi Stats, FastAPI has over 9 million monthly downloads, surpassing even full-stack frameworks like Django.

Source: kinsta.com

3 Web Frameworks to Use With Python

myapp/ is the main directory of your FastAPI application. It includes all the other files and directories needed for the application.static/ is a directory used to store static assets such as CSS, JavaScript, and image files. These assets are served directly by the web server and are typically used to add visual styling and interactivity to the application.css/, img/, js/...

Source: www.stratascratch.com

Best Alternatives to FastAPI App Free for Windows (2021)

FastAPI Alternative – So many alternatives app to FastAPI that you must to know out there. And, looking for an ideal software was not easy matter. Lucky you, at this page you can find the best replacement app for FastAPI. So what you are waiting for, get the latest FastAPI alternative app for Windows 10 from this page.

Source: alternativetoapp.com

Top 5 Back-End Frameworks to Consider for Web Development in 2021

FastAPI is a modern, fast (high-performance), web framework for building APIs with Python 3.6+ based on standard Python type hints. It is fast when compared to other major Python frameworks like Flask and Django. FastAPI gives great flexibility to fulfill businesses’ API needs in today’s evolving world.

Source: www.fissionlabs.com

Social recommendations and mentions

Based on our record, FastAPI seems to be a lot more popular than Meltano. While we know about 312 links to FastAPI, we've tracked only 26 mentions of Meltano. 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.

Meltano mentions (26)

AI product development is being held back by data engineering
Hey HN, Arch CEO here! Our team has been working at the intersection of data engineering and software engineering for a few years now with Meltano (https://meltano.com), and this year, the rise in Generative AI has made it clear that the bottleneck in unlocking the potential value of data has shifted from data integration on data teams to data engineering on software teams, so we’ve decided to do something about... - Source: Hacker News / almost 3 years ago
How useful is Airbytes in production pipelines?
We use Meltano for (EL) and Prefect for scheduling. Is not click-ops, but works very well for us! Behind the scenes Meltano wraps up Singer spec similarly like Airbyte does with its connectors. Before that we tried Airbyte (~5 months ago?) and it was so bad.. We could not choose the columns to replicate and the connectors were unstable i.e. Skipping data, all sort of odd errors and so on.. Source: about 3 years ago
Ask HN: Who is hiring? (May 2023)
Meltano's all-remote team and community of thousands are on a mission to enable everyone to realize the full potential of their data. To this end, we are bringing software engineering best practices to data teams in the form of an open-source DataOps platform that we envision becoming the foundation of every team's ideal data stack. Our public company handbook (https://handbook.meltano.com/) has all the details on... - Source: Hacker News / over 3 years ago
Ask HN: Who is hiring? (April 2023)
Meltano | Full-Time | Remote | https://meltano.com Meltano's all-remote team and community of thousands are on a mission to enable everyone to realize the full potential of their data. To this end, we are bringing software engineering best practices to data teams in the form of an open-source DataOps platform that we envision becoming the foundation of every team's ideal data stack. Our public company handbook... - Source: Hacker News / over 3 years ago
If dbt is the "T" part of an "ELT", what do you use for "EL"?
We switched from AWS Glue to Meltano for the EL part of ELT and it's been a joy to use. We're moving so much faster now. Source: over 3 years ago

FastAPI mentions (312)

I Built My First Machine Learning API — Here's Everything I Learned
I used FastAPI, a Python framework built specifically for creating APIs quickly, with automatic validation and interactive documentation baked in. - Source: dev.to / 30 minutes ago
Shipping Sovereign SDK: Cryptographic Forensic Receipts and the End of the AI "Prose Tax"
The Sovereign SDK is a Python-native framework designed to minimize prose overhead while generating ironclad, cryptographic execution receipts for AI agents, complete with drop-in FastAPI/Starlette ASGI middleware. - Source: dev.to / 3 months ago
5-Minute AI Jobs and Closed Tabs — Why We Built Replay-Then-Tail SSE
We had a feature in production where a single user request could run for five-plus minutes — fetch documents, chunk them, hit an LLM per chunk, synthesize a final answer. We did the obvious thing first: a FastAPI handler that ran the pipeline and streamed progress back to the browser over Server-Sent Events. - Source: dev.to / 3 months ago
FastAPI With LangChain and MongoDB
FastAPI is a Python framework for building APIs quickly, efficiently, and with very little code. - Source: dev.to / 4 months ago
I Built A " CrowdSense AI " : A Scalable, Context-Aware Platform for Smart Stadiums
Backend: Python-based FastAPI for its asynchronous I/O capabilities and rapid JSON serialization. - Source: dev.to / 4 months ago