IQueryable vs IEnumerable in C#: Difference, Examples & Which Is Better (Beginner Guide)

f you’re new to C# and LINQ, two interfaces cause big confusion: IEnumerable<T> and IQueryable<T>. This guide explains them like you’re brand-new, with simple code, clear rules, and SEO-friendly answers to “What is IQueryable vs IEnumerable,” “difference between them,” and “which is better.”

Quick Summary

• IEnumerable<T> → works in memory (LINQ to Objects). Best when the data is already loaded (Lists, Arrays, Dictionaries).
• IQueryable<T> → builds a query for the data source (LINQ to SQL/EF Core). Best for databases/remote APIs; lets the server do the heavy lifting.
• Both are deferred: they run when you enumerate (e.g., foreach, ToList()).

What is IEnumerable<T>?

• Think “loop through items I already have.”
• Runs inside your app.
• Great for small/medium in-memory collections.

var numbers = new List<int> { 1, 2, 3, 4, 5 };
// IEnumerable<T>: filters in memory
IEnumerable<int> evens = numbers.Where(n => n % 2 == 0);

foreach (var n in evens) // executes on enumeration
    Console.WriteLine(n);

Use it when: the data is already in memory or you need C#-only operations after loading.

What is IQueryable<T>?

• Think “compose a query; let the DB do work.”
• Builds an expression tree that Entity Framework Core (or another LINQ provider) translates to SQL.
• Filters/sorts on the server, so you fetch only what you need.

// EF Core example
IQueryable<User> users = dbContext.Users;

var recent = users
    .Where(u => u.IsActive && u.CreatedAt >= DateTime.UtcNow.AddDays(-7))
    .Select(u => new { u.Id, u.Email });

var list = await recent.ToListAsync(); // SQL runs here

Use it when: querying databases/remote sources, especially large datasets.

Key Differences: IQueryable vs IEnumerable (Table)

Which Is Better?

It depends on where your data lives.

• Choose IQueryable<T> for databases or big datasets → better performance, less memory, less network I/O.
• Choose IEnumerable<T> for in-memory work or when you intentionally need client-side logic.

Pro tip: Start queries as IQueryable<T>, materialize late with ToListAsync(). If you must run a custom C# method, switch at the last moment:

var query = dbContext.Products
    .Where(p => p.Price > 100)      // server
    .Select(p => new { p.Id, p.Name });

var result = (await query.ToListAsync()) // materialize
    .OrderBy(p => FancyRank(p.Name))     // client-only
    .ToList();

Common Pitfalls (and Easy Fixes)

1. Client evaluation by accident
   • Symptom: Slow queries, high memory usage.
   • Fix: Keep non-translatable methods after materialization (ToList()/AsEnumerable()).
2. Multiple DB hits
   • Symptom: Query runs several times.
   • Fix: Cache with ToList() if you need to iterate more than once.
3. Using IEnumerable<T> against a database
   • Symptom: Loads too much data into memory.
   • Fix: Start from DbSet<T> as IQueryable<T> and filter first.

Example: Count active users (server-side)

int count = await dbContext.Users
    .Where(u => u.IsActive)
    .CountAsync();

Example: After materialization, use C#-only logic

var names = (await dbContext.Users
        .Where(u => u.IsActive)
        .Select(u => u.Name)
        .ToListAsync())        // DB work done
    .Where(NameLooksSpecial);  // pure C# predicate

FAQ (Quick Answers)

What is the difference between IQueryable and IEnumerable in C#?
IEnumerable<T> runs in memory for already-loaded collections. IQueryable<T> composes queries that run on the data source (e.g., SQL via EF Core), sending back only the needed results.

Which is better: IQueryable or IEnumerable?
For database queries and large datasets, IQueryable<T> is better. For in-memory collections or when you need C#-only operations, use IEnumerable<T>.

Interview Questions (Use in Tech Screens)

1. Explain how IQueryable<T> uses expression trees.
   What happens if the LINQ provider can’t translate a method to SQL? Give an example and the impact on performance.
2. When would you switch from IQueryable<T> to IEnumerable<T> using AsEnumerable() or ToList()?
   Describe the risks of switching too early vs. too late.

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