Each year, renowned IT consulting firm Gartner researches and compiles reports based on their findings of current market trends in a wide variety of industries. Published as Magic Quadrants, these results highlight the top vendors in each category and point out both strengths and challenges they might face.
Although the 2020 Gartner Magic Quadrant for Data Integration Tools isn’t drastically different from past years, the technologies and tools have evolved, giving certain vendors a leading edge against their nearest competitors.
What are “Data Integration Tools”?
Gartner defines data integration as “a discipline comprising the practices, architectural techniques and tools that allow organizations to ingest, transform, combine and provision data across the spectrum of data types.”
This integration of tools is key to meeting the data consumption requirements of all business processes and applications in the enterprise and beyond. Some examples of technology that would fall under the integration tool umbrella include those that address:
- Data processing
- Data replication
- Data ingestion
- Data pipelining
- Stream data integration
- Data fabrics
- Data virtualization
- Data engineering
In order to qualify for inclusion in this quadrant, vendors must offer:
- A process that includes batch or bulk data movement.
- The ability to deploy any data integration styles, including the capability to work in conjunction with application services.
- Data virtualization that provides logical views of the data.
- Data replication which copies schema and data from one location in a physical repository to another.Data synchronization that focuses on the establishment and maintenance between two independently managed CRUD instances of a shared data model.
- Stream data integration that includes the ability to incorporate inferred row-to-row integrity as well as event models, and any variations of either of these.
Magic Quadrant for Data Integration Tools 2020
Here is the 2020 Magic Quadrant for Data Integration Tools:
