Difference Between Polybase and Linked Server in SQL Server

Polybase in MS SQL Server:

1. SQL 2016 and subsequent versions introduce the Polybase functionality.

2. Structured and unstructured data from a variety of sources, including Hadoop, Azure Blob Storage, and SQL Server itself, may be integrated seamlessly.

3. Enables users to access and analyze data using conventional SQL syntax by offering a uniform query interface.

4. Uses a distributed query execution approach to load and query data in parallel, improving speed.

5. Eliminates the need for specialized coding and simplifies the data integration procedure.

6. Supports the processing of enormous amounts of data from many sources.

7. Allows for the exploration and study of data using well-known SQL queries.

8. By utilizing the current SQL Server infrastructure, offers improved performance and cost benefits.

9. Its use may be constrained in some circumstances by a lack of data source support.

10. Steps in configuration and setup may be difficult for people with little technical knowledge.

Linked Server in MS SQL Server:

1. SQL Server has a functionality called Linked Server.

2. Creates a direct link between SQL Server and other database management systems.

3. Allows users to utilize SQL Server Management Studio or other client tools to run queries on distant databases.

4. Suitable for combining data from many relational databases or when real-time database synchronization is needed.

5. Allows for flexible data access and manipulation across several database systems.

6. Supports distributed queries and table joining across several database architectures.

7. Enables the synchronization of data in real time between databases.

8. Helps make migration during database projects easier.

9. Requires unique setup and configuration for every connected server connection.

10. The amount of data being transported and the network latency can both affect performance.

Summary:

When deciding between Polybase and Linked Server, it's crucial to take our unique requirements into account as well as the kind of our data sources. Considering aspects including data volume, source kinds, real-time demands, and general integration requirements can help us decide which strategy is best. Both have advantages and drawbacks.