Top 15 Advance SQL inteview questions

Top 15 Advanced SQL Interview Questions for .NET Professionals (2026 Edition)

As we move into 2026, the role of a senior .NET developer has transcended beyond simple CRUD operations. With the proliferation of distributed systems, AI-integrated databases, and cloud-native architectures, senior technical interviews now focus on high-scale data integrity, performance tuning, and modern SQL features. This guide covers the top 15 advanced SQL interview questions designed to test your architectural depth and implementation skills within the .NET ecosystem.

1. How do Window Functions differ from GROUP BY clauses in high-performance reporting?

Window functions allow you to perform calculations across a set of table rows that are somehow related to the current row, without collapsing the result set into a single row. This is vital for 2026 data analytics where real-time streaming data needs context (like moving averages or running totals) without losing the individual transaction details.

// Using EF Core to execute a Window Function via Raw SQL
var report = await _context.Orders
    .FromSqlRaw(@"SELECT OrderId, Amount, 
                  SUM(Amount) OVER (PARTITION BY CustomerId ORDER BY OrderDate) as RunningTotal
                  FROM Orders")
    .ToListAsync();

2. Explain the use cases and performance implications of Recursive Common Table Expressions (CTEs).

Recursive CTEs are essential for querying hierarchical data structures, such as organizational charts or multi-level category trees in e-commerce platforms. In 2026, they are often used to traverse graph-like structures within relational databases before handing data off to AI models.

// C# example: Calling a stored procedure that uses a recursive CTE
// for an organizational hierarchy
public async Task<List<EmployeeNode>> GetOrgStructureAsync(int managerId)
{
    return await _context.Employees
        .FromSqlInterpolated($"EXEC GetEmployeeHierarchy {managerId}")
        .ToListAsync();
}

3. Describe the "N+1 Query Problem" and how to identify it using modern .NET profiling tools.

The N+1 problem occurs when an application makes N additional database calls to fetch related data for every primary record retrieved. In modern .NET (EF Core 10+), we mitigate this using Eager Loading (Include), Explicit Loading, or Query Splitting for large datasets to avoid Cartesian product explosions.

// Optimization: Using AsSplitQuery() to avoid Cartesian explosion in EF Core
var blogs = await _context.Blogs
    .Include(b => b.Posts)
    .Include(b => b.Contributors)
    .AsSplitQuery() // 2026 Best Practice for complex relationships
    .ToListAsync();

4. How do Vector Indexes work in SQL Server (2025+ versions) and how do they integrate with Semantic Kernel?

In 2026, SQL Server has robust support for Vector types to support RAG (Retrieval-Augmented Generation). Vector indexes allow for "Nearest Neighbor" searches on embeddings generated by LLMs. Senior developers must know how to store these embeddings as `VECTOR` data types and query them using cosine similarity.

// Storing and querying vector embeddings in .NET
public async Task<List<Product>> FindSimilarProducts(float[] embedding)
{
    string vectorJson = JsonSerializer.Serialize(embedding);
    return await _context.Products
        .FromSqlInterpolated($"SELECT TOP 5 * FROM Products ORDER BY VECTOR_DISTANCE(Embedding, {vectorJson}, 'cosine')")
        .ToListAsync();
}

5. What is the difference between Snapshot Isolation and Read Committed Snapshot Isolation (RCSI)?

RCSI provides statement-level consistency, while Snapshot Isolation provides transaction-level consistency. In high-concurrency .NET applications, RCSI is often enabled at the database level to prevent readers from blocking writers without the overhead of full serializability.

6. Explain the concept of "Columnstore Indexes" and when to use them over B-Tree indexes.

Columnstore indexes store data by column rather than by row. This is the gold standard for OLAP (Analytical) workloads in 2026. While B-Tree (Clustered) indexes are best for finding specific records, Columnstore indexes are optimized for scanning large datasets and performing aggregations.

7. How do you implement Optimistic Concurrency in EF Core using RowVersion/Timestamp?

To prevent the "last-in-wins" scenario in distributed systems, we use a `rowversion` column. EF Core automatically checks this version during `SaveChangesAsync()`, throwing a `DbUpdateConcurrencyException` if the record has been modified by another process.

// Entity Configuration
public class Product {
    public int Id { get; set; }
    [Timestamp]
    public byte[] Version { get; set; } // Database-managed rowversion
}

// Handling the exception in C#
try {
    await _context.SaveChangesAsync();
} catch (DbUpdateConcurrencyException ex) {
    // Logic to resolve conflict (merge or reload)
}

8. Discuss the use of Temporal Tables for auditing and point-in-time recovery.

Temporal tables (System-Versioned tables) allow SQL Server to automatically track the history of data changes. This is highly relevant for 2026 compliance standards (GDPR, SOC2), allowing developers to query what data looked like at any specific timestamp directly through EF Core.

// Querying a Temporal Table in EF Core
var historicalProduct = await _context.Products
    .TemporalAsOf(DateTime.UtcNow.AddMonths(-1))
    .SingleAsync(p => p.Id == productId);

9. How do Query Interceptors in EF Core help in performance monitoring?

Interceptors allow you to inject custom logic into the execution of SQL commands. In 2026, they are commonly used for dynamic sharding, fine-grained logging, or automatically adding query hints for specific performance scenarios.

// A simple Command Interceptor for logging slow queries
public class SlowQueryInterceptor : DbCommandInterceptor {
    public override ValueTask<DbDataReader> ReaderExecutingAsync(
        DbCommand command, CommandEventData eventData, DbDataReader result) {
        if (eventData.Duration > TimeSpan.FromSeconds(2)) {
            // Log slow query details
        }
        return base.ReaderExecutingAsync(command, eventData, result);
    }
}

10. What are the advantages of JSON Path expressions in SQL for modern microservices?

With the shift toward Document-Relational hybrids, SQL Server's ability to query JSON stored in `NVARCHAR(MAX)` or the native `JSON` type (introduced in recent versions) allows microservices to store semi-structured data while maintaining the ACID guarantees of a relational database.

11. Explain "Deadlock Victim" selection and how to minimize deadlocks in high-traffic APIs.

SQL Server chooses a deadlock victim based on the "Deadlock Priority" or the cost of rolling back the transaction. To minimize this in .NET, ensure that all transactions access tables in the same order, keep transactions short, and use appropriate isolation levels.

12. How does Distributed SQL (like Azure SQL Managed Instance or Cosmos DB for PostgreSQL) affect query design?

In 2026, scaling horizontally is common. Developers must design queries with "Distribution Keys" (Sharding keys) in mind. A query that doesn't include the distribution key may result in a "cross-shard fan-out," significantly degrading performance in a distributed environment.

13. Describe the difference between Materialized Views and Standard Views.

Standard views are virtual and run the underlying query every time. Materialized views (Indexed Views) store the result set physically. In 2026, these are used for complex aggregations in dashboards where data is updated frequently but read-latency must be sub-millisecond.

14. How do you handle "Bulk Operations" in EF Core without performance degradation?

Native EF Core now supports `ExecuteUpdate` and `ExecuteDelete`, which perform set-based operations directly on the database without loading entities into memory. This is a critical performance optimization for senior developers.

// Bulk Update in EF Core (2026 approach)
await _context.Products
    .Where(p => p.Category == "Legacy")
    .ExecuteUpdateAsync(s => s.SetProperty(p => p.IsActive, false));

15. What is the "Parameter Sniffing" problem and how do you resolve it?

Parameter sniffing occurs when SQL Server creates an execution plan based on the first parameter value passed, which might not be optimal for subsequent values. This is resolved using query hints like `OPTIMIZE FOR UNKNOWN` or `RECOMPILE`, or by using local variables within stored procedures.

Mastering these advanced SQL concepts is essential for navigating the complex data landscape of 2026. By understanding the intersection of deep database internals and the .NET runtime, you can build systems that are not only functional but also exceptionally scalable and performant. Advanced technical proficiency in SQL remains the most significant differentiator for senior software professionals in the modern era.