DV traditionally serves BI and analytics needs. It provides access to any data source instantly – even real-time. This is an important advantage over traditional BI solutions, that typically depend on a predefined data warehouse in which your operational data is replicated. The structure is costly and time consuming to alter, and as data usually is loaded periodically the data is not real-time. DV allows to connect to new data sources in a fraction of the time and have real-time access to them – an important advantage in an era where timely availability of data is crucial.
AM supports your IT development and external parties to easily connect to you IT landscape for secure access of functionality and data of your existing applications. It hands your integration department the instruments to efficiently create standardized interfaces, and to provide documentation and functionality for consumers to register in order to adopt the API. This allows you or external parties to build instantly (web)-applications and executable business processes that leverage your current IT and service landscape: A vendor may invoke a function to check your inventory directly, employees may be offered a self-service web-application based on an existing HR system, and an order-to-pay process over systems may be automated.
DV typically allows the BI department to provide access to data for real time analysis swiftly, this way supporting BI analysts.
AM supports the IT integration department to provide standard building blocks and to open new business channels. Your development department and business partners benefit as they may realize automated business solutions faster and more efficiently.
AM allows data to flow bi-directionally: It both allows to read data from applications and inserting data by triggering application transactions.
DV is typically intended to query data for analytical purposes. Note that though some DV solutions offer functionality to alter data directly as well, this is discouraged from data governance perspective.
AM typically delivers API-s. These “Application Programming Interfaces” can be leveraged by most development environments to easily access the applications data and functionality. Usually the webservice standard REST is used, though SOAP not is supported commonly as well.
DV typically delivers data in database-view-like format, consisting of virtual tables that can be accessed using standard database techniques. BI-analysts can directly use them in their analytics and report tooling. DV may provide complex views for specific purposes, combining data from several sources. Note that most recent DV product support API-s as output as well.
AM typically realizes an “wrapper” around existing applications and web-services. Consumers access this wrapper to request data or to trigger transactions on the underlaying applications. Note that several AM products support the access to other data sources as well, like database.
DV supports virtually any data source. Think of databases, data lakes, several kinds of files and data warehouses, but also -like AM- application and web services through their API-s.
A key functionality of AM is metering: It measures the actual usage of the API-s. This allows for accounting functions like billing (“pay per use”). It may support SLA guarding and fair-use policies as well. e.g. through limiting access (“throttling”) when a consumer exceeds certain quota.
Typically, DV does not support metering. Though it may optimize performance by technical measures (e.g. data caching).
AM has an external focus. Therefor it comes with extensive security features: It offers means to setup secure connections and data exchange. Next it monitors and logs all access and it allows to define policies regarding to usage. Throttling may be used in case a consumer exceeds specific limits.
As DV has a internal focus it generally does not come with extensive security features. It relies on the internal facilities. Access is generally monitored and logged though.
The list above emphasizes that though Data Virtualization and API Management have similar goals they are complementary technologies. Applying DV and AM provide you with strong data capabilities, both for your decisioning and analytics processes on one hand and operational and supply chain processes on the other.
But benefits exceed the sum of the advantages of both technologies:
DV would benefit from AM, as its API-s would allow DV to exploit application data for analytics purposes even more efficiently. And more: AM would make it possible to expose DV data through API management and use it in your automated processes. Or even share it with business partners: Either for free, or exploiting metering to make it a paid service (“Data as a Service”)
AM in its turn can may profit from the strong data integration capabilities of DV: They allows to easily define a set of API-s based on combined data from any number of data sources. This prevents the need for the integration department to develop expensive integration services.