2010 Gartner Magic Quadrant for Data Integration Tools

IT leaders focused on data integration competencies must be aware of key trends and developments in the data integration tools market. During 2010, organizations continued to emphasize cost-effectiveness (a balance of functionality and value relative to cost), broader usage (with increased emphasis on data migration, master data management, and operational application integration scenarios), and high-quality customer service and support. Vendors responded in various ways, including new pricing and delivery models, and greater transparency in pricing. The desire for "good enough" technology at attractive price points drove interest in lower-cost and open-source solutions. At the same time, consolidation in this and related markets caused preferences to shift toward incumbent providers of applications or other information management infrastructure. Despite these trends, several providers focused primarily on data integration (independent of applications or business intelligence offerings) and continue to fare well despite growing competitive pressure. Many providers expanded their support for styles of data integration beyond bulk/batch, tightened their links to data quality tools, and moved toward a model-driven approach leveraging common metadata across their suites. These developments indicate growing maturity in this market relative to Gartner's vision and buyers' desires. In addition, as convergence with the related market of data quality tools continued to progress, an emphasis on governance began to emerge and some data integration practitioners began to emphasize data quality with higher priority than the mechanics of integration. The increasing maturity of the data integration tools and data quality tools markets and the rapidly growing overlap between them (in terms of both providers and buyers) signals the pending arrival of complete market convergence. Further trends emerging or advancing in 2010 and impacting this market included attention to problems of extreme data volumes (with many vendors exploring and some delivering Hadoop-based deployment models) and cloud-based data integration services.