DBSEDec 18, 2019

Data Services with Bindaas: RESTful Interfaces for Diverse Data Sources

arXiv:1912.08768v11 citations
Originality Incremental advance
AI Analysis

This addresses the burden for developers in building high-performance, secure APIs for diverse data sources, though it is incremental as it builds on existing middleware and RESTful interface concepts.

The paper tackles the problem of developing custom interfaces for heterogeneous data management systems by presenting Bindaas, a secure, extensible big data middleware that provides uniform RESTful access, resulting in negligible overheads and efficient handling of concurrent requests in production healthcare environments.

The diversity of data management systems affords developers the luxury of building systems with heterogeneous systems that address needs that are unique to the data. It allows one to mix-n-match systems that can store, query, update, and process data, based on specific use cases. However, this heterogeneity brings with it the burden of developing custom interfaces for each data management system. Developers are required to build high-performance APIs for data access while adopting best-practices governing security, data privacy, and access control. These include user authentication, data authorization, role-based access control, and audit mechanisms to avoid compromising the security standards mandated by data providers. In this paper, we present Bindaas, a secure, extensible big data middleware that offers uniform access to diverse data sources. By providing a standard RESTful web service interface to the data sources, Bindaas exposes query, update, store, and delete functionality of the data sources as data service APIs, while providing turn-key support for standard operations involving security, access control, and audit-trails. Bindaas consists of optional features, such as query and response modifiers as well as plugins that implement composable and reusable data operations on the data. The research community has deployed Bindaas in various production environments in healthcare. Our evaluations highlight the efficiency of Bindaas in serving concurrent requests to data source instances. We further observe that the overheads caused by Bindaas on the data sources are negligible.

Code Implementations1 repo
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