Research scientists in data-intensive science use a variety of scientific software applications to support their analyses and processes. To efficiently support the work of these scientists, software applications should satisfy the essential requirements of interoperability, integration, automation, reproducibility, and efficient data handling. Various enabling technologies including workflow, service, and portal can be used to address these essential requirements. Through an in-depth review, this chapter illustrates that no one technology can address all of the essential requirements of scientific processes and therefore necessitates the use of hybrid technologies to support the requirements of data-intensive research. The chapter also describes current scientific applications that utilize a combination of technologies and discusses some future research directions.