Microsoft SQL Server supports a concept similar to sharding

Microsoft SQL Server provides several built-in features to achieve horizontal partitioning of data across multiple databases or servers, which aligns with the sharding paradigm:

Federated Databases (Manual Sharding)

•  What it is: Distribute tables across multiple SQL Server instances manually (e.g., CustomerDB_Server1, CustomerDB_Server2).
•  How to query: Use linked servers or application logic to route queries.
•  Limitations: Complex to manage; no built-in load balancing.

 Partitioned Tables (Vertical Scaling)

• What it is: Split a single table into partitions within the same database (e.g., by date ranges).

• Syntax Example:
      CREATE PARTITION FUNCTION myRangePF (datetime)
      AS RANGE RIGHT FOR VALUES ('2023-01-01', '2024-01-01');

• Limitations: Still runs on a single server; no horizontal scaling.

Elastic Database Tools (Azure SQL Database)

• What it is: A cloud-native solution for sharding in Azure SQL Database.

• Features:
          Shard Map Manager: Tracks shards and routes queries.
          Elastic Query: Query across shards seamlessly.
          Split/Merge: Dynamically resize shards.

• Limitations: Only works in Azure (not on-premises SQL Server).

Distributed Partitioned Views (Legacy)

• What it is: Combine data from multiple tables (on different servers) into a single view.

• Syntax Example:
     CREATE VIEW CustomersAll AS
         SELECT * FROM Server1.CustomerDB.dbo.Customers
         UNION ALL
         SELECT * FROM Server2.CustomerDB.dbo.Customers;

• Limitations: Performance overhead; deprecated in favor of Azure Elastic Database tools.