Data is Increasingly acknowledged as a strategic asset. It is required by organization to survive in a world that cries for agility, transparency and the power to act. Data Virtualization (DV) and API Management (AM) are two technologies that respond to this need. Therefore, they are in the spotlights today. Both DV and AM aim to provide you an effective, efficient, and controlled access to your data.

The benefits over a custom way of disclosing your data are plenty:

It minimizes time and effort to share data between your systems, users and external parties. All it takes them is to “plug in”! Consumers need not bother where data is produced or stored. No need for you to provide them direct access to your systems and data stores: If implemented well the consumer only sees and gets the data where he or she is entitled to. And if you like to change or replace underlying systems, no problem: If you keep the DV and AM interfaces intact changes are transparent to them.

Data Virtualization and API Management are largely complementary technologies and may very well applied together as a happy couple. In order to understand this, this article will explain the differences between both concepts.

Intention

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.

Users

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.

Data Flow

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.

Output

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.

Data Sources

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.

Operation

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).

Security

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.

Summarizing: Data Virtualization and API management gain focus thanks to the awareness of the value data as an asset. Separately they offer a lot of power to exploit data. However, in conjunction they are an unbeatable couple to support you becoming a more effective, data driven, agile and cost-efficient organization.