Why is Dictionary preferred over Hashtable in C#?
Data Structures & Algorithms practice on Codemia
Step through 300 algorithm problems with animated visualisers that show the data structure changing as the code runs.
In C#, both Dictionary and Hashtable are collection data types used to store information in key-value pairs. However, Dictionary is often preferred over Hashtable due to several reasons primarily related to type safety, performance, and generality of use. In this article, we delve deep into why developers might choose Dictionary over Hashtable, include technical explanations, examples, and summarize with a comparison table.
Understanding Hashtable and Dictionary
Hashtable, introduced in the initial version of .NET Framework, is a collection that stores key-value pairs in a hash table format. Dictionary, on the other hand, is a generic collection introduced in .NET 2.0, allowing for more type safety and other benefits.
Type Safety
Hashtable is a non-generic type, which means it can store keys and values of any type (object type). This can lead to runtime errors if there is a type mismatch or if you need to perform operations specific to the data type stored. Here's a simple example that highlights type safety issues with Hashtable:
Dictionary<TKey, TValue>, being a generic collection, resolves this issue as you define the types of the key and value at compile-time:
Performance
The performance of Dictionary is generally better than Hashtable due to the avoidance of boxing and unboxing. Boxing is the process of converting a value type to an object type, which happens in Hashtable since it stores keys and values as object. Unboxing is the reverse process. These operations are computationally costly and can be avoided with generic collections like Dictionary.
Flexibility and Use with Linq
Another advantage of Dictionary is its compatibility with LINQ (Language Integrated Query), which can be incredibly useful to perform more complex queries and manipulations. Hashtable does not directly support LINQ, requiring additional steps (like casting each element) to use it effectively with LINQ.
Easily Manage Null Values
Managing null values in Dictionary is more straightforward because it allows null for nullable types and reference types (but not for non-nullable value types like int, double, etc). Hashtable can also store null, but being loosely typed, it can lead to more complex error-checking and handling code.
Serialization
Dictionary supports XML serialization natively while Hashtable does not, unless you implement a custom serialization mechanism. This makes Dictionary a better choice for applications that require serialization of data for storage, communication, or configuration purposes.
Summary Table
Here’s a summary of the key differences between Dictionary and Hashtable:
| Feature | Hashtable | Dictionary |
| Type Safety | Non-generic | Generic (type-specific) |
| Performance | Lower (boxing/unboxing) | Higher (no boxing/unboxing) |
| Compatibility with LINQ | Supported via casting | Native support |
| Null Value Management | Loose type checking | Strict type checking, supports null |
| Serialization | Custom implementation required | Supports XML serialization |
Conclusion
Dictionary in C# is generally preferred over Hashtable primarily due to the strong type safety, better performance, and seamless integration with newer language features like LINQ. Hashtable might still be used in older codebases or when interacting with APIs that require it, but for most modern development scenarios, Dictionary provides a more robust, efficient, and safer option for handling key-value pair collections.
Related reading
- Why is Dictionary preferred over Hashtable in C?
- Why is dictionary so much faster than list?
- Why is Dictionary.First so slow?
- Why is faster than list?
- Why is HashSetPoint so much slower than HashSetstring?
- Why is HttpClient BaseAddress not working?
- Why is Git not considered a block chain?
- Why is Insertion sort better than Quick sort for small list of elements?

DSA Fundamentals
Master algorithmic patterns and data structures through hands-on LeetCode-style problems - from arrays and hashing to dynamic programming and advanced graphs.
View the courseTrack what you have practised
A free account saves your progress, solutions and study plan across every problem on Codemia.
Data Structures & Algorithms practice on Codemia
Step through 300 algorithm problems with animated visualisers that show the data structure changing as the code runs.