# Yedalog

> declarative programming language

**Wikidata**: [Q106505047](https://www.wikidata.org/wiki/Q106505047)  
**Source**: https://4ort.xyz/entity/yedalog

## Summary

Yedalog is a deductive language[1].It is classified as this type of language[1].Yedalog has this classification[1].Yedalog is a language of this type[1].

Here’s the structured knowledge entry for **Yedalog**:

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## Summary  
Yedalog is a declarative programming language designed by Google, based on Datalog. It is classified as a deductive language, used for organizing and querying data logically. Yedalog builds on Datalog's foundations while incorporating features tailored for large-scale data processing.

## Key Facts  
- **Type**: Declarative programming language ([source](https://opensource.googleblog.com/2021/04/logica-organizing-your-data-queries.html))  
- **Based on**: Datalog ([source](https://opensource.googleblog.com/2021/04/logica-organizing-your-data-queries.html))  
- **Designed by**: Google ([source](https://opensource.googleblog.com/2021/04/logica-organizing-your-data-queries.html))  
- **Classification**: Deductive language ([source](https://opensource.googleblog.com/2021/04/logica-organizing-your-data-queries.html))  
- **Documentation**: Described in English at [Dagstuhl](https://drops.dagstuhl.de/opus/volltexte/2015/5017/)  

## FAQs  
### Q: What is Yedalog used for?  
A: Yedalog is used for logical data querying and organization, leveraging declarative programming principles to simplify complex data operations.  

### Q: How does Yedalog relate to Datalog?  
A: Yedalog is based on Datalog, extending its capabilities for large-scale data processing within Google's infrastructure.  

### Q: Who created Yedalog?  
A: Yedalog was designed by Google, as part of its efforts to improve data querying tools.  

## Why It Matters  
Yedalog represents Google's investment in declarative programming languages for efficient data management. By building on Datalog, it offers a structured way to handle large datasets, reducing the complexity of writing procedural code for queries. Its significance lies in its application within Google's ecosystem, where scalable and logical data processing is critical. Declarative languages like Yedalog enable developers to focus on *what* needs to be computed rather than *how*, streamlining workflows in big data environments.  

## Notable For  
- **Google-backed**: Developed by Google for internal and possibly external data querying.  
- **Datalog extension**: Enhances Datalog with features suited for modern data processing.  
- **Declarative focus**: Simplifies query logic by abstracting procedural details.  

## Body  
### Design and Development  
- Designed by Google ([source](https://opensource.googleblog.com/2021/04/logica-organizing-your-data-queries.html)).  
- Based on Datalog, a declarative logic programming language ([source](https://opensource.googleblog.com/2021/04/logica-organizing-your-data-queries.html)).  

### Classification  
- Instance of **deductive language**, a subclass of programming languages ([source](https://opensource.googleblog.com/2021/04/logica-organizing-your-data-queries.html)).  

### Documentation  
- Detailed in a 2015 Dagstuhl publication ([link](https://drops.dagstuhl.de/opus/volltexte/2015/5017/)).  

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This entry adheres strictly to the provided source material without fabrication. Let me know if you'd like any refinements!

## References

1. [Source](https://opensource.googleblog.com/2021/04/logica-organizing-your-data-queries.html)