Data access with REST APIs
Blog|by James Roberts|20 August 2019
Data access methods have changed over the years as applications and the data environment they interact with have increased in complexity. Applications which used to connect to a single relational database are being replaced by apps which quite likely depend on a number of heterogeneous data sources, both on premises and in the cloud. The use of BI, IoT, AI, ML and contextual information adds to the likelihood of a complex data landscape where security and integration can be difficult to solve.
With the adoption of modular and service orientated approaches to building applications, the use of APIs has become common place. For a long time, the combination of SQL and ODBC/JDBC has been the primary method used by developers working with data. APIs are now playing a significant role in data access too – but the disparate nature of APIs can be problematic.
The OData standard (Open Data Protocol) defines best practice for building and consuming RESTful APIs for handling data. Tableau, Salesforce, Tibco, Telerik, Informatica and Excel are examples of applications that work with OData. The protocol makes it easier to work with the variables that APIs introduce such as request and response headers, status codes, HTTP methods, URL conventions, media types, payload formats, queries etc. From a developer’s perspective, things are simplified if the data source’s REST interface is based on OData standards.
REST APIs provide important security features to support access policies, authentication and data masking. These have become a priority for data architects but can be challenging to implement. This is especially true if you’re an ISV and lack resources to develop and maintain your own connectors and keep abreast with the latest developments. Furthermore, the familiar tools used with SQL don’t always sit well with REST APIs.
Progress is a specialist provider of drivers for data access. Their DataDirect Autonomous REST Connector addresses the need for seamless, real-time connectivity between REST data, ODBC/JDBC tools and applications. The connector decreases the amount of time required for applications to understand and consume APIs through its codeless configuration and intelligent sampling. It acts as a middleman, allowing SQL dialogue to take place with the client application while handling RESTful communications with the data access tier and coding environment. This allows you to query API data using standard SQL. The connector normalises the semi-structured JSON response data into structured data which can then be used with SQL. This eliminates the need to understand the complexities of the JSON response.
Read the Whitepaper created by Progress to find out more about their DataDirect Autonomous REST Connector.
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