Big news from Google. They have just launched a brand-new programming language called Mangle. And trust me, it’s something that could completely change how developers work with databases. So, in this article, we’re going to break it all down for you, what exactly Mangle is, its cool and unique features, how it’s different from other programming languages out there, and why it actually matters for anyone working with data or tech. So stick around because by the end you will understand why everyone’s talking about Mangle and why it could be a game-changer.
Here is the official link to Google Mangle Repository.
Mangle
Mangle is a programming language for deductive database programming. It is an extension of Datalog, with various extensions like aggregation, function calls and optional type-checking.
Deductive database programming is useful for bringing data from multiple data sources together since it enables us to represent and query that data in a uniform way. It can also be used to model domain knowledge, similar to machine-readable ontology but without being restricted to binary predicates.
Datalog is an expressive declarative language similar to relational calculus (think SQL and relational views). Unlike relational calculus, it also supports recursive rules and program structuring in a straightforward way.
Mangle contains Datalog as a fragment and adds extensions that make its use more practical. Some of the good properties like guaranteed termination are lost when such extensions are used.
The goal of Mangle as an open source project is to convey the concepts in a way…
What Is Mangle?
Let’s start by understanding what Mangle actually is. In simple words, Mangle is a programming language made by Google specifically for working with databases. But it’s not just any database language. It’s designed for something called deductive database programming. Don’t worry, that just means it’s really good at finding answers from complex data by reasoning through it, almost like thinking step by step.
Mangle is built on top of Datalog, which is a well-known logic programming language, but Google has made it much more powerful by adding features that make it easier to handle big and complicated data sets. And just so you know, Google officially launched Mangle on August 22, 2025.
The main goal here? Google wants to make it way easier and faster for developers to ask questions, analyze, and reason over complex data sets without writing tons of complicated code. So basically, it’s about making data smarter and simple to work with.
What Makes Mangle So Powerful
Now let’s talk about what makes Mangle so powerful. Mangle is built on top of Datalog, which is already a powerful language for working with logical queries and databases. Datalog lets you ask questions of your data in a very structured way, but it has its limits when data sets get large or complicated.
Mangle takes that foundation and makes it much stronger by adding features that help developers handle more complex problems without writing endless lines of code.
Aggregation Support
One of the coolest things about Mangle is its aggregation support. This means you can easily calculate things like sums, averages, and counts directly within your queries. For example, if a company has user data spread across multiple databases, and you want to find the total number of users, Mangle lets you do that in one query without manually combining the data. It saves time and makes the process much more efficient.
Function Calls Inside Queries
Another important feature is the ability to include function calls inside your queries. This allows developers to run custom calculations or logic right in the middle of fetching data. So if you need to perform special operations like converting values or applying business rules, Mangle handles it seamlessly, keeping everything in one place.
Optional Type Checking
Mangle also provides optional type checking, which acts like a safety net to ensure your data is consistent and correct. If you want to make sure numbers, dates, and text are all in the right format, Mangle can check that automatically. But if you prefer more flexibility, you can skip this step, giving you control over how strict the system should be.
Recursive Rules
One of the most powerful aspects of Mangle is its support for recursive rules. This means queries can refer to themselves, which is incredibly useful for tasks like tracking paths in a network or analyzing hierarchies such as an organization chart or a social network.
Working Across Different Databases
Combined with its ability to query multiple databases consistently, Mangle makes it easier to work across different sources of data without worrying about compatibility issues.
Complex Analysis and Reasoning
Finally, Mangle is designed for complex analysis and reasoning. It can handle sophisticated tasks like understanding relationships in complex knowledge systems (also known as ontologies) and performing in-depth data analysis that combines different types. This makes Mangle a very versatile tool, allowing the developers to solve problems that would otherwise require multiple programs or complicated coding logic.
How Mangle Compares to Other Languages
Now that we have seen what Mangle can do and its main features, let’s take a closer look at what really makes it stand out compared to other programming and query languages that developers are already familiar with.
You can take SQL for an example. SQL is great for asking questions from a database, but when you need to do complex reasoning or work with very large and interconnected data sets, it becomes harder to manage and less expressive.
On the other hand, developers often turn to Python with libraries to handle advanced data tasks. Python is flexible and powerful, but it’s not a declarative language, which means you often have to write a lot of code to tell the program how to do something rather than just what you want.
Mangle changes the game by being declarative, recursive, and highly flexible all in one package. You can express complex queries simply, include recursive logic, and even perform aggregation right inside the language. It also allows seamless integration with different data sets without extra work.
Essentially, Mangle lets you do advanced data reasoning without getting lost in complicated code, making it a smarter and faster way to handle complex data tasks.
Real-World Uses of Mangle
Now that we know what makes Mangle different and powerful, let’s see where it can actually be used in the real world. Understanding its applications will help you see why it’s such an important tool for developers and data experts.
- Data Integration: Many companies have data scattered across multiple databases or systems. Bringing it all together for analysis can be a huge headache. Mangle makes this easy by allowing developers to query multiple sources in a consistent and straightforward way.
- Graph Analysis: Graphs store relationships between things, like social networks or organizational structures. Thanks to Mangle support for recursive rules, it can efficiently handle queries that need to explore these complex connections.
- Ontology Reasoning: This is about understanding and working with relationships in complex knowledge systems. It’s particularly useful in AI and data modeling, where you need to reason about how different pieces of information relate to each other.
- Complex Data Analysis: Aggregation, function calls, and multi-source data handling make Mangle perfect for industries like finance, technology, research, and AI, where data sets are large, varied, and interconnected.
In short, Mangle gives developers a smart and flexible way to solve real-world data problems, making advanced analysis simpler, faster, and more reliable
How to Get Started With Mangle
Now that we have seen what Mangle can do and how it’s used, you might be wondering, okay, how can I actually start using it? Let’s break that down.
Getting started with Mangle is simpler than you might think. Google has made it available as an open-source project on GitHub, which means anyone can access it for free.
Inside the repository, you will find everything you need to start exploring Mangle. This includes:
The source code (to see how Mangle works under the hood)
Examples that demonstrate how to write queries
Detailed documentation to guide you step by step
For beginners, a great way to start is by experimenting with sample queries. Try asking questions from small data sets, play with aggregation functions, or even combine data from multiple sources to see how Mangle handles it. As you get comfortable, you can gradually move to more complex data sets and advanced queries.
Wrapping It Up
With Mangle, Google is giving developers a powerful new way to work with complex data, and exploring it now could really give you an edge in your coding and data projects.
So go ahead, test it, experiment with it, and see what Google Mangle can do for you.
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Top comments (1)
So go ahead, test it, experiment with it, and see what Google Mangle can do for you.