Methods for Data Shaping with Pipelines

In a CREATE PIPELINE statement

Low

Easiest

Pros: Generally, runs the fastest of the three data shaping methods; transactional guarantees. Cons: Limited to SQL WHERE CLAUSE to perform filtering and SQL expressions to perform other shaping logic; can only load data into one target table; cannot perform lookups in other tables; a single row in the data source cannot generate multiple rows in the target table.

CREATE PIPELINE uses the LOAD DATA clause to perform data shaping. See examples in the LOAD DATA topic.

Pipeline Stored Procedure

Medium

More Difficult

Pros: Transactional guarantees; cons of specifying data shaping logic directly in your CREATE PIPELINE statement don’t apply. Cons: Limited to the capabilities of the MPSQL language; cannot use third-party libraries.

See examples in CREATE PIPELINE ... INTO PROCEDURE

Transform

High

Most Difficult

Pros: Can use any nearly any programming language and leverage third-party libraries. Cons: Not available in SingleStoreDB Cloud; runs slower than stored procedures for most use cases; deployment could be challenging; cannot insert into multiple tables; transactional guarantees apply to data written to stdout, only (refer to the guide in the next column for details).

See the guide Writing a Transform to Use With a Pipeline