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CData JDBC Driver for Google BigQuery 2019

CData JDBC Driver for Google BigQuery 2019 - Build 19.0.7354

Overview

The CData JDBC Driver for Google BigQuery 2019 offers the most natural way to connect to Google BigQuery data from Java-based applications and developer technologies. The driver wraps the complexity of accessing Google BigQuery data in an easy-to-integrate, 100%-Java JDBC driver. Applications can then access Google BigQuery as a traditional database. The driver hides the complexity of accessing data and provides additional powerful security features, smart caching, batching, socket management, and more.

Key Features

  • Deploy a single JAR that does not rely on client-side libraries.
  • Write SQL to retrieve and update Google BigQuery data.
  • Compliant with JDBC 3.0 and JDBC 4.0.
  • Codeless integration with popular BI, reporting, and ETL tools.

Getting Started

See Getting Started for A-Z guides on authenticating and connecting to Google BigQuery data. See the Google BigQuery integration guides for information on connecting from other applications.

Using the JDBC Driver

See Using JDBC for examples of using standard JDBC classes like DataSource, Connection, Statement, ResultSet, and others, to work with Google BigQuery data. Using JDBC (from Tools) walks through the steps of integration with JDBC tools, using several popular database tools as examples.

Schema Discovery

See Schema Discovery to access schema information through the standard JDBC interfaces. Query the System Tables to access additional metadata, such as data source capabilities.

JDBC Remoting

See JDBC Remoting to configure remote access to the JDBC data source. The JDBC remoting feature allows hosting the JDBC connection on a server to enable connections from virtually anywhere -- various clients on any platform (Java, .NET, C++, PHP, Python, and so on) and using any standards-based technology (ODBC, JDBC, and so on). JDBC remoting is enabled using the popular MySQL wire protocol server.

SQL Compliance

See SQL Compliance for a syntax reference and code examples outlining the supported SQL.

Caching Data

See Caching Data to configure replication and caching for a range of scenarios common to remote data access. Configurations include:

  • Autocache: Automatically cache data to a lightweight database. Save data for later offline use or enable fast reporting from the cache.
  • Replication: Copy data to local and cloud data stores such as Oracle, SQL Server, Google Cloud SQL, and so on. The replication commands allow for intelligent incremental updates to cached data.
  • No caching: Work with remote data only. No local cache file is created.

Data Model

See Data Model for information on the available entities and how to query them.

Connection String Options

The Connection properties describe the various options that can be used to establish a connection.

 
 
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Build 19.0.7354.0