Connectors/Learn

What is a BigID Connector

BigID Connectors allow your BigID system to provide insights about new types of data. Whether that's a known data type like CSV from a new type of data source or something completely new to the BigID ecosystem, a connector will allow you to bring BigID's data discovery capabilities to that system.

Why do we need connectors?

Every data source has its own way of communicating with third parties. Some data sources return information nicely organized, others return it as a jumbled mess. In order for BigID to give you the insights you expect, data needs to be fed to BigID in a consistent way. Connectors work as translators between the multitude of formats that data sources have adapted to the standard format BigID expects. Note that even if the data format is the same (REST JSON, REST XML, GraphQL, etc) small differences make it difficult to reuse connectors. Think of a connector as a way to interface with a single system.

How are connectors implemented?

Connectors can either be implemented as a REST API or as a Java JAR file. REST connectors are bound by the limitations of HTTP connections including timeouts, size limitations and more. Java connectors are well suited for complex use cases especially those involving data sources that stream data.

BigID Scanning Process

While BigID has different scanning methods (snapshots, metadata scans, Hyperscan), they all depend on scanners. Scanners allow BigID to contact data sources and create the search maps that are used to power the BigID system. Depending on your deployment model you may have scanners located in the BigID cloud, on-premise, or in your organization's cloud provider accounts. Scanners take the form of a Docker container and require only outbound network access.

In a scan, the scanner will do the following:

- If correlation is enabled, load all correlation records in order to find them within data sources. - Scan metadata