Data and software are at the heart of every business. However for many organizations, realizing the full potential of the digital economy remains a significant challenge. Since the inception of MongoDB, we’ve understood that the biggest challenges developers face are related to working with data:
Demands for higher productivity and faster time to market are being held back by rigid relational data models that are mismatched to modern code and impose complex interdependencies among engineering teams. ° Organizations are unable to work with or extract insights from, the massive and rapidly growing amount of data generated by modern applications, including time series, geospatial, and polymorphic data. ° Monolithic and fragile legacy databases are inhibiting the wholesale shift to distributed systems and cloud computing that deliver the resilience and scale demanded by digital businesses and support new regulatory demands for data privacy. ° Previously separate transactional, analytical, search and mobile workloads are converging to create rich data-driven applications and customer experiences. However, each workload has traditionally been powered by its own database, creating duplicated data silos stitched together with fragile ETL pipelines, accessed by different developer APIs.
