3 years ago

Category: Database, Data, artificial-intelligence

Elasticsearch is a distributed, RESTful, full-text search engine designed to store, index, retrieve, and manage document-oriented or semi-structured data. Common uses for Elasticsearch range from building a simple search engine for a web site or document collection, to supporting auto-completion, analytics, AI, and cognitive computing workloads.

In this article, we explore how CData drivers: CData Drivers for Elasticsearch provide unmatched access to Elasticsearch with many features beyond those available from the native drivers.

When querying the data, the native Elasticsearch driver returns a single table with one column, 'text': In contrast, CData Drivers expose two separate related tables, with several columns, including foreign keys to define the relationships: CData Drivers provide support for querying JSON structures, like arrays and nested JSON objects, which can often be found in Elasticsearch records.

Beyond these major features and key differentiators, CData Drivers for Elasticsearch come with additional features, that are included across all of the full range of data sources that CData supports.