How .NET 10 Helps Developers Write More Complex LINQ Queries

With Real-World Problems & Solutions

LINQ is one of the most powerful features in the .NET ecosystem. It allows developers to express database logic using clean, readable C# code. But as applications grow in complexity — with multi-table joins, nested data, JSON columns, AI embeddings, and bulk operations — traditional LINQ begins to show limitations.

With the release of .NET 10 and EF Core 10, developers now have much more expressive power in LINQ, enabling them to solve complex, real-world problems with cleaner syntax and better performance.

In this blog, we’ll walk through:

✔ Real-world problem scenarios
✔ The limitations of older EF/LINQ
✔ How .NET 10 solves them
✔ Complete code examples

Let’s dive in.

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1. Problem: Writing LEFT JOINs in LINQ Was Always Painful

Scenario

You’re building an ERP-style Reports module. You need a list of all customers — including those who have no orders yet.

In SQL, this is trivial:

SELECT c.Name, o.OrderNo
FROM Customers c
LEFT JOIN Orders o ON c.Id = o.CustomerId;

But in older versions of LINQ, LEFT JOIN required awkward syntax:

var result = from c in db.Customers
             join o in db.Orders on c.Id equals o.CustomerId into temp
             from t in temp.DefaultIfEmpty()
             select new { c.Name, OrderNo = t?.OrderNo };

Hard to read. Hard for junior developers. More code than SQL.

---

Solution in .NET 10: Native LeftJoin and RightJoin Support

EF Core 10 introduces built-in LeftJoin() and RightJoin() methods.

var result = db.Customers
    .LeftJoin(
        db.Orders,
        c => c.Id,
        o => o.CustomerId,
        (c, o) => new 
        {
            CustomerName = c.Name,
            OrderNo = o?.OrderNo
        })
    .ToList();

Why This Matters

• Cleaner, readable syntax

• Matches SQL directly

• Easier for beginners

• Reduces bugs during JOIN transformations

This is one of the biggest quality-of-life improvements in LINQ to date.

---

2. Problem: Bulk Updating Thousands of Records Was Slow

Scenario

Your system needs to automatically update the status of all users who haven’t logged in for 90 days.

Traditionally, EF required:

1. Query records

2. Loop each entity

3. Update C# object

4. Save changes

Slow. Memory-heavy. Not scalable.

---

Solution in .NET 10: ExecuteUpdate With Real Logic Inside

EF Core 10 allows you to run bulk updates directly in the database, and now supports normal C# logic inside the update expression.

await db.Users
    .Where(u => u.LastLogin < DateTime.UtcNow.AddDays(-90))
    .ExecuteUpdateAsync(setter =>
    {
        setter.SetProperty(u => u.Status, “Inactive”);
        setter.SetProperty(u => u.UpdatedOn, DateTime.UtcNow);
    });

Why This Matters

• No entity is loaded into memory

• Executes as a single SQL UPDATE command

• Supports conditional logic inside the update

• Extreme performance improvements

Perfect for scheduled jobs, reporting systems, CRON operations, cleanup services, etc.

---

3. Problem: Stored JSON Data Was Hard to Query Directly

Scenario

You have a UserSettings JSON column in SQL Server:

{
  “theme”: “dark”,
  “notifications”: {
    “email”: true,
    “sms”: false
  }
}

You want to fetch users with dark theme enabled.

Before .NET 10, this required:

• Raw SQL

• Client-side evaluation

• Custom value converters

None of these scale well.

---

Solution in .NET 10: Native JSON Column Support

EF Core 10 understands SQL Server’s native JSON data type, and maps complex types to JSON automatically.

var users = db.Users
    .Where(u => u.Settings.Theme == “dark”)
    .ToList();

Why This Matters

• Fully LINQ-to-JSON translation

• Update JSON fields without loading the whole object

• Store rich data structures with fewer tables

Perfect for microservices, user preference storage, metadata-heavy systems, and AI apps.

---

4. Problem: Writing Complex WHERE IN Queries Affected Performance

Scenario

You need to fetch products for a list of 500 product IDs.

var products = db.Products
    .Where(p => productIds.Contains(p.Id))
    .ToList();

EF would generate 500 parameters → SQL plan cache pollution → slower queries under heavy usage.

---

Solution in .NET 10: Parameterized Collection Mode

EF Core 10 introduces smarter handling of collections:

• Uses batched parameters

• Pads parameters for stable query plans

• Reduces SQL server recompilation

Developer Benefit

No code changes needed — you just get better performance automatically.

---

5. Problem: Global Query Filters Were Hard to Control

Scenario

You have multiple global filters:

• Soft delete

• Tenant isolation

• Country restriction

On some queries, you want:

✔ Only soft delete
❌ No tenant filter

Previously, EF only allowed enabling/disabling all filters.

---

Solution in .NET 10: Named Query Filters

You can give each filter a name and ignore them selectively:

var orders = db.Orders
    .IgnoreQueryFilters(”TenantFilter”)
    .ToList();

Why This Matters

• More flexible multi-tenant applications

• Better domain-driven design support

• Cleaner architecture

Now your queries behave exactly how you want.

---

6. Problem: AI Vector Search Required Custom SQL or NoSQL Datastores

Scenario

You store embeddings for semantic search:

float[] Embedding;

You want to query by similarity:

“Find the 10 most similar documents.”

Before .NET 10:

• You needed PostgreSQL + pgvector

• Raw SQL queries

• No LINQ support

---

Solution in .NET 10: Native Vector Data Type

var result = db.Documents
    .OrderBy(d => EF.Functions.VectorDistance(d.Embedding, queryVector))
    .Take(10)
    .ToList();

Why This Matters

• AI search without external databases

• Fully LINQ-based semantic search

• Better performance inside SQL Server

This opens the door to AI-powered features inside .NET systems without complex integrations.

---

7. Problem: Complex Value Objects Required Too Many Tables

Scenario

You have a Customer entity with nested properties:

public Address ShippingAddress { get; set; }

In older EF:

• Required separate table mappings

• Harder migrations

• More joins → slower queries

---

Solution in .NET 10: Complex Types Done Right

Now EF can store this as:

• Table-splitted columns, or

• JSON, or

• Inline embedded columns

And you can query properties directly:

var customers = db.Customers
    .Where(c => c.ShippingAddress.City == “Dhaka”)
    .ToList();

Developer Benefit

Cleaner domain models that match real-world objects.

---

Final Thoughts

.NET 10 dramatically enhances how developers write LINQ queries. With support for:

✅ Native Left/Right Join
✅ Bulk updates with real logic
✅ JSON column queries
✅ Named query filters
✅ Vector similarity search
✅ Complex types
✅ Smarter collection handling

…LINQ is now powerful enough to handle large-scale enterprise systems, data-heavy applications, and AI-integrated features — all while staying developer-friendly.

For More, Follow The GitHub repository: DotNet10Features