
Codacy
SonarQube
CodeClimate
CodeFactor.io
ESLint
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codebeat
SiftingIO
Twelve Data
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Polygon.io
FinFeedAPI
Finage
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FinancialData.net
Codacy automates code reviews and monitors code quality on every commit and pull request reporting back the impact of every commit or pull request, issues concerning code style, best practices, security, and many others. It monitors changes in code coverage, code duplication and code complexity. Saving developers time in code reviews thus efficiently tackling technical debt. JavaScript, Java, Ruby, Scala, PHP, Python, CoffeeScript and CSS are currently supported. Codacy is static analysis without the hassle.
SiftingIO is an API-first market data platform built for financial applications, trading tools, dashboards, research platforms, and enterprise data workflows.
The platform helps teams access consistent market data across multiple asset classes using unified JSON schemas, multi-venue aggregation, REST APIs, WebSocket streams, SDKs, and developer-ready documentation.
SiftingIO is designed for teams that need real-time quotes, historical data, OHLCV candles, trades, reference data, and scalable integration patterns without maintaining separate vendor feeds for each market.
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SiftingIO's answer:
SiftingIO is built on a modern API and data infrastructure for real-time and historical market data delivery.
The platform uses technologies and engineering patterns around:
The focus is on building a reliable data infrastructure that can serve financial applications, dashboards, trading tools, research systems, and enterprise workflows.
SiftingIO's answer:
SiftingIO is built around a simple idea: market data should be easier to integrate, but not simplified to the point where it becomes unreliable.
The platform combines real-time and historical data across multiple asset classes under one API structure. Teams can work with stocks, FX, crypto, commodities, DEX, and on-chain markets without maintaining separate schemas, authentication models, and integration logic for each source.
What makes SiftingIO different is the engineering layer behind the API:
This makes SiftingIO useful for teams that care not only about accessing data, but also about keeping their data infrastructure clean and scalable.
SiftingIO's answer:
SiftingIO is a strong choice for teams that need market data across more than one asset class and want to avoid maintaining multiple vendor integrations.
Many financial applications start with one market, then expand into others. A team may begin with FX or crypto, then later need stocks, commodities, DEX data, or on-chain metrics. SiftingIO is designed for that kind of growth.
Key reasons to choose SiftingIO:
The main value is not only data access. It is reducing the engineering cost of using market data across financial products.
SiftingIO's answer:
SiftingIO is built for technical and data-driven teams working with financial market data.
The primary audience includes:
SiftingIO is especially useful for teams that need both real-time and historical data, or teams that work across multiple asset classes and want a consistent API model instead of separate vendor-specific integrations.
SiftingIO's answer:
SiftingIO was created from hands-on experience building and operating financial data infrastructure.
Market data integrations often become more complex as products grow. Each asset class can come with different data formats, different delivery methods, different authentication models, and different assumptions about symbols, timestamps, quotes, trades, and history.
SiftingIO was built to reduce that complexity.
The goal is to provide a consistent market data API that helps teams access real-time and historical data across multiple asset classes without rebuilding their integration every time they add a new market.
The product reflects an engineering-first approach: clean API design, unified schemas, REST and WebSocket support, multi-venue aggregation, and infrastructure that can support production financial workflows.
SiftingIO's answer:
SiftingIO does not publicly list customer names unless they are approved for disclosure.
The platform is designed for financial applications, trading tools, dashboards, research platforms, quantitative teams, fintech companies, and enterprise data workflows that need real-time or historical market data through APIs.
Based on our record, Codacy seems to be more popular. It has been mentiond 4 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.
I'm trying to use Codacy to review my code. One of the issues is regarding the use of the "setcookie" function. Source: over 4 years ago
Does anyone have an example on how to get this conversion done on github actions where I can convert the *.coverage file into a *.xml file for uploading to codacy.com. Source: about 5 years ago
Online analysisFinally, if you want a simple way to analyze your code without having to manually configure everything locally, you can use an online code review service such as Codacy (shameless plug here). We already integrate some of the mentioned detection tools in this article and we are working every day to improve the service. The other main benefit of using automated code review tools is to allow you to... - Source: dev.to / over 5 years ago
Because you care and because you always want to be better, automation is a great way to optimize your review workflow process. Go ahead and do a quick search on Google for automated code reviews and see who better fits your workflow. You'll find Codacy on your Google search and we hope you like what we do. - Source: dev.to / over 5 years ago
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