JDBC

Azure Data Lake Storage JDBC Driver

Easily connect live Azure Data Lake Storage data with Java-based BI, ETL, reporting, AI/ML & custom apps.

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The Azure Data Lake Storage JDBC Driver enables users to connect with live Azure Data Lake Storage , directly from any applications that support JDBC connectivity. Rapidly create and deploy powerful Java applications that integrate with Azure Data Lake Storage.

Azure Data Lake Storage

Azure Data Lake Storage JDBC Connectivity Features

SQL access to Azure Data Lake operational data
Compatible with Gen1 and Gen2 instances
Connect to live Azure Data Lake Storage data, for real-time data access with the Azure Data Lake Storage Python Connectors
Full support for data aggregation and complex JOINs in SQL queries
Secure connectivity through modern cryptography, including TLS 1.2, SHA-256, ECC, etc.
Seamless integration with leading BI, reporting, and ETL tools and with custom applications via the Azure Data Lake Storage Connector.

Target Service, API

The driver connects to Azure Data Lake Storage Gen2. Hierarchical namespace storage.

Schema, Data Model

Models ADLS Gen2 filesystem as tables. Files and directories with ACLs.

Key Objects

Filesystems, Directories, Files, and ACLs. Full data lake storage access.

Operations

Read and write operations. SQL queries on file metadata. Permission management.

Authentication

Azure AD, account key, or SAS token authentication. ABFS protocol support.

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Azure Data Lake Storage JDBC Driver Download

JDBC access to Azure Data Lake Storage

Full-featured and consistent SQL access to any supported data source through JDBC

Certified Compatibility*

Our drivers undergo extensive testing and are certified to be compatible with leading analytics and reporting applications like SAP Crystal Reports, Pentaho, Business Objects, Crystal Reports and many more.
Metadata Discovery

Full support for JDBC DatabaseMetaData provides extensive schema discovery capabilities. Explore tables, columns, keys, and other data constructs based on user identity.
Developer Friendly

Design-time support for all major Java IDEs, including Eclipse, IntelliJ, and NetBeans.
JDBC Remoting

Our exclusive remoting feature allows hosting the JDBC connection on a server to enable connections from various clients on any platform (Java, .NET, C++, PHP, Python), using any standards-based technology (ODBC, JDBC, etc.). JDBC Remoting is enabled using the popular MySQL wire protocol server.
Replication and Caching

Our replication and caching commands make it easy to copy data to local and cloud data stores such as Oracle, SQL Server, Google Cloud SQL, etc. The replication commands include many features that allow for intelligent incremental updates to cached data.

String, Date, Numeric SQL Functions

The driver includes a library of over 50 functions that can manipulate column values into the desired result. Popular examples include Regex, JSON, and XML processing functions.
Collaborative Query Processing

Our drivers enhance the data source's capabilities by additional client-side processing, when needed, to enable analytic summaries of data such as SUM, AVG, MAX, MIN, etc.
Easily Customizable and Configurable

The data model exposed by our JDBC Drivers can easily be customized to add or remove tables/columns, change data types, etc. without requiring a new build. These customizations are supported at runtime using human-readable schema files that are easy to edit.
Secure Connectivity

Includes standard Enterprise-class security features such as TLS/ SSL data encryption for all client-server communications.

See what you can do with Azure Data Lake Storage JDBC Driver

Data integration & ETL

Integrate Azure Data Lake Storage into your systems and data warehouses through popular Java-based ETL/EAI tools. Supports both self-hosted environments and cloud service deployment.

and more

BI, reporting & data virtualization

Connect to Azure Data Lake Storage from any JDBC-compatible BI, reporting, and data virtualization platform. Provides seamless integration using SQL as the standard query interface across all tools.

and more

Custom Java applications

Use the Azure Data Lake Storage JDBC Driver to rapidly deliver Java-based applications that connect with Azure Data Lake Storage. Universal SQL-based interactivity simplifies integration and speeds time to market.

and more

Connect to Azure Data Lake Storage—empower every team

Management & data consumer team
- CData JDBC Drivers for Azure Data Lake Storage act as if they are a native connector for your ETL, BI, and data virtualization tools.
- Organizations can connect to new services to capture a full view of the business, or migrate to modern data technology while maintaining connections to existing systems.
- Speed up your AI initiative with CData. Connect your data with the AI / ML platform of your choice.
IT Team

Need to integrate your internal systems with Azure Data Lake Storage? CData JDBC Drivers let you do it easily. Java-based applications can connect to Azure Data Lake Storage with SQL/JDBC—any ETL, EAI (Enterprise Application Integration), or ESB (Enterprise Service Bus) can connect to Azure Data Lake Storage.
ISVs & cloud service vendors for embedded JDBC
- Embed CData JDBC Drivers for Azure Data Lake Storage in your product and differentiate with your connectivity.
- Standard SQL access. Stop researching different authentication, data models, and query methods.
- Use your resources to build your product—CData takes care of your connectivity.
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AI-assisted development with CData CLI

Build Azure Data Lake Storage integrations faster with AI that understands your schema

Schema-aware AI

CData CLI gives AI coding tools access to your Azure Data Lake Storage schema. No more guessing table names or column types—AI sees the same metadata in your JDBC Drivers.

Your AI knows SQL

How to find table names, column names, and how to generate SQL syntax are things that AI knows well from millions of training data. No need for customization, no hallucinations. Your AI acts like a domain specialist to Azure Data Lake Storage.

More accurate, more token-efficient

With CData CLI's queryable schema detection and highly efficient queries with filters, aggregation, joins with correct pushdown, your AI will achieve more accuracy with less token usage.

Supported AI Coding Tools

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FAQs

Frequently asked Azure Data Lake Storage JDBC driver questions

Learn more about Azure Data Lake Storage JDBC drivers for data and analytics integration

Can Azure Data Lake Storage be used with Java?

Yes, Azure Data Lake Storage can be used with Java . CData provides a JDBC type 4/5 driver for Azure Data Lake Storage that allows Java applications to connect to Azure Data Lake Storage using standard JDBC APIs. This driver enables you to execute SQL queries, manage connections, and process data stored in Azure Data Lake Storage from Java, or any Java-based application that supports JDBC.
Does Azure Data Lake Storage support JDBC?
Not natively. However, CData offers a JDBC driver for Azure Data Lake Storage that allows you to connect to Azure Data Lake Storage data from any Java-based application that supports JDBC, just like you would access a traditional database. This can be useful for tasks like:
- Accessing Azure Data Lake Storage from applications: Connect to Azure Data Lake Storage data in popular tools and applications including Informatica, Talend, Apache Spark, Apache NiFi, and many others.
- Real-time data: You can work with live Azure Data Lake Storage data within these applications, enabling tasks like reporting and analysis.
- Connecting systems: Build data integrations between Azure Data Lake Storage and other systems.
The Azure Data Lake Storage JDBC driver is a pure Java type 4/5 driver with comprehensive ANSI SQL-92 support. This means that virtually any application that can connect to data via JDBC, can use the CData JDBC driver for real-time integration. Download a fully functional free trial of the Azure Data Lake Storage JDBC driver today to get started.
Is there a JDBC driver for Azure Data Lake Storage?

Yes, the CData JDBC driver for Azure Data Lake Storage provides universal JDBC data connectivity for Azure Data Lake Storage. The Azure Data Lake Storage JDBC driver offers a simple SQL-based layer of abstraction that simplifies real-time data access for users and applications, enabling them to communicate with Azure Data Lake Storage using a standardized set of functions. Virtually any application on any platform can use the CData JDBC driver for real-time integration.
How do I connect to Azure Data Lake Storage via JDBC?

Connectivity to Azure Data Lake Storage via JDBC is easy. First, download and install the Azure Data Lake Storage JDBC driver.

Once the installation is complete, navigate to the JDBC driver documentation page. Here, you'll find a wealth of information about the installed driver. The step-by-step instructions for creating a DSN and using it to connect to Azure Data Lake Storage via JDBC are just the beginning. The documentation also provides extensive configuration details for using the Azure Data Lake Storage JDBC driver with all your favorite applications and development tools, ensuring you have all the support you need.
Where can I download a JDBC driver for Azure Data Lake Storage?

All of the CData JDBC drivers, including the Azure Data Lake Storage JDBC driver are available for download online. To get started, download a fully functional free trial of the Azure Data Lake Storage JDBC driver today.
How do I install the JDBC driver for Azure Data Lake Storage?

To install the Azure Data Lake Storage driver, simply download one of the Azure Data Lake Storage JDBC driver installers available online. The installers are comprehensive setup utilities that will install all the components required to use the Azure Data Lake Storage JDBC driver on your system.