Azure Data Lake Storage Drivers & Connectors
for Data Integration

Connect to Azure Data Lake Storage from BI, analytics, and reporting tools through standards-based drivers. Easily integrate Azure Data Lake Storage data with BI, Reporting, Analytics, ETL Tools, and Custom Solutions.


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BI & Analytics



Our drivers offer the fastest and easiest way to connect real-time Azure Data Lake Storage data with BI, analytics, reporting and data visualization technologies. They provide unmatched query performance, comprehensive access to Azure Data Lake Storage data and metadata, and seamlessly integrate with your favorite analytics tools.

LEARN MORE: Connectivity for BI & Analytics

Popular BI & Analytics Integrations



Alteryx Designer: Prepare, Blend, and Analyze Azure Data Lake Storage in Alteryx Designer (ODBC) Amazon QuickSight: Build Interactive Dashboards from Azure Data Lake Storage Data in Amazon QuickSight Aqua Data Studio: Connect to Azure Data Lake Storage in Aqua Data Studio AWS Databricks: Process & Analyze Azure Data Lake Storage Data in Databricks (AWS) Birst: Build Visualizations of Azure Data Lake Storage in Birst BIRT: Design BIRT Reports on Azure Data Lake Storage Clear Analytics: Build Charts with Azure Data Lake Storage in Clear Analytics DBxtra: Build Dashboards with Azure Data Lake Storage in DBxtra Domo: Create Datasets from Azure Data Lake Storage in Domo Workbench Dundas BI: Build Dashboards with Azure Data Lake Storage in Dundas BI Excel (on Mac OS): Work with Azure Data Lake Storage Data in MS Excel on Mac OS X FineReport: Feed Azure Data Lake Storage into FineReport IBM Cognos BI: Create Data Visualizations in Cognos BI with Azure Data Lake Storage Infragistics Reveal: Analyze Azure Data Lake Storage Data in Infragistics Reval JasperServer: Create Azure Data Lake Storage Reports on JasperReports Server Jaspersoft BI Suite: Connect to Azure Data Lake Storage in Jaspersoft Studio JReport Designer: Integrate with Azure Data Lake Storage in JReport Designer Klipfolio: Create Azure Data Lake Storage-Connected Visualizations in Klipfolio KNIME: Enable the Azure Data Lake Storage JDBC Driver in KNIME LINQPad: Working with Azure Data Lake Storage in LINQPad Microsoft SSAS: Build an OLAP Cube in SSAS from Azure Data Lake Storage MicroStrategy: Connect to Live Azure Data Lake Storage Data in MicroStrategy through Connect Server MicroStrategy: Use the CData JDBC Driver for Azure Data Lake Storage in MicroStrategy Microstrategy Desktop: Use the CData JDBC Driver for Azure Data Lake Storage in MicroStrategy Desktop Microstrategy Web: Use the CData JDBC Driver for Azure Data Lake Storage in MicroStrategy Web OBIEE: Azure Data Lake Storage Reporting in OBIEE with the Azure Data Lake Storage JDBC Driver pandas: Use pandas to Visualize Azure Data Lake Storage in Python Pentaho Report Designer: Integrate Azure Data Lake Storage in the Pentaho Report Designer Power BI Desktop: Author Power BI Reports on Real-Time Azure Data Lake Storage Power BI Service: Visualize Live Azure Data Lake Storage Data in the Power BI Service Power Pivot: Access Azure Data Lake Storage Data in Microsoft Power Pivot Power Query: Access Azure Data Lake Storage Data in Microsoft Power Query QlikView: Connect to and Query Azure Data Lake Storage in QlikView over ODBC R: Analyze Azure Data Lake Storage in R (JDBC) R: Analyze Azure Data Lake Storage in R (ODBC) RapidMiner: Connect to Azure Data Lake Storage in RapidMiner Redash: Build Azure Data Lake Storage-Connected Dashboards in Redash SAP Analytics Cloud: Analyze Azure Data Lake Storage Data in SAP Analytics Cloud SAP Business Objects: Create an SAP BusinessObjects Universe on the CData JDBC Driver for Azure Data Lake Storage SAP Crystal Reports: Publish Reports with Azure Data Lake Storage in Crystal Reports SAS: Use the CData ODBC Driver for Azure Data Lake Storage in SAS for Real-Time Reporting and Analytics SAS JMP: Use the CData ODBC Driver for Azure Data Lake Storage in SAS JMP Sisense: Visualize Live Azure Data Lake Storage in Sisense Spago BI: Connect to Azure Data Lake Storage in SpagoBI Tableau: Visualize Azure Data Lake Storage in Tableau Desktop Tableau Cloud: Build Azure Data Lake Storage Visualizations in Tableau Cloud Tableau Server: Publish Azure Data Lake Storage-Connected Dashboards in Tableau Server TIBCO Spotfire: Visualize Azure Data Lake Storage in TIBCO Spotfire through ADO.NET TIBCO Spotfire: Visualize Azure Data Lake Storage Data in TIBCO Spotfire TIBCO Spotfire Server: Operational Reporting on Azure Data Lake Storage from Spotfire Server

ETL, Replication, & Warehousing



From drivers and adapters that extend your favorite ETL tools with Azure Data Lake Storage connectivity to ETL/ELT tools for replication — our Azure Data Lake Storage integration solutions provide robust, reliable, and secure data movement.

Connect your RDBMS or data warehouse with Azure Data Lake Storage to facilitate operational reporting, offload queries and increase performance, support data governance initiatives, archive data for disaster recovery, and more.


Popular Data Warehousing Integrations



Amazon Redshift: Automated Continuous Azure Data Lake Storage Replication to Amazon Redshift Amazon S3: Automated Continuous Azure Data Lake Storage Replication to Amazon S3 Apache Airflow: Bridge Azure Data Lake Storage Connectivity with Apache Airflow Apache Camel: Integrate with Azure Data Lake Storage using Apache Camel Apache Cassandra: Automated Continuous Azure Data Lake Storage Replication to Apache Cassandra Apache Kafka: Automated Continuous Azure Data Lake Storage Replication to Apache Kafka Apache NiFi: Bridge Azure Data Lake Storage Connectivity with Apache NiFi Apache NiFi Batch Operations: Perform Batch Operations with Azure Data Lake Storage Data in Apache NiFi Azure Synapse: Automated Continuous Azure Data Lake Storage Replication to Azure Synapse BIML: Use Biml to Build SSIS Tasks to Replicate Azure Data Lake Storage to SQL Server CloverDX: Connect to Azure Data Lake Storage in CloverDX (formerly CloverETL) Couchbase: Automated Continuous Azure Data Lake Storage Replication to Couchbase CSV: Automated Continuous Azure Data Lake Storage Replication to Local Delimited Files Databricks: Automated Continuous Azure Data Lake Storage Replication to Databricks FoxPro: Work with Azure Data Lake Storage in FoxPro Google AlloyDB: Automated Continuous Azure Data Lake Storage Replication to Google AlloyDB Google BigQuery: Automated Continuous Azure Data Lake Storage Replication to Google BigQuery Google Cloud SQL: Automated Continuous Azure Data Lake Storage Replication to Google Cloud SQL Google Data Fusion: Build Azure Data Lake Storage-Connected ETL Processes in Google Data Fusion Heroku / Salesforce Connect: Replicate Azure Data Lake Storage for Use in Salesforce Connect HULFT Integrate: Connect to Azure Data Lake Storage in HULFT Integrate IBM DB2: Automated Continuous Azure Data Lake Storage Replication to IBM DB2 Informatica Cloud: Integrate Azure Data Lake Storage in Your Informatica Cloud Instance Informatica PowerCenter: Create Informatica Mappings From/To a JDBC Data Source for Azure Data Lake Storage Jaspersoft ETL: Connect to Azure Data Lake Storage in Jaspersoft Studio Microsoft Access: Automated Continuous Azure Data Lake Storage Replication to Microsoft Access Microsoft Azure Tables: Automated Continuous Azure Data Lake Storage Replication to Azure SQL Microsoft Power Automate: Build Azure Data Lake Storage-Connected Automated Tasks with Power Automate (Desktop) MongoDB: Automated Continuous Azure Data Lake Storage Replication to MongoDB MySQL: Automated Continuous Azure Data Lake Storage Replication to MySQL Oracle Data Integrator: ETL Azure Data Lake Storage in Oracle Data Integrator Oracle Database: Automated Continuous Azure Data Lake Storage Replication to Oracle petl: Extract, Transform, and Load Azure Data Lake Storage in Python PostgreSQL: Automated Continuous Azure Data Lake Storage Replication to PostgreSQL Replicate to MySQL: Replicate Azure Data Lake Storage to MySQL with PowerShell SAP HANA: Automated Continuous Azure Data Lake Storage Replication to SAP HANA SingleStore: Automated Continuous Azure Data Lake Storage Replication to SingleStore SnapLogic: Integrate Azure Data Lake Storage with External Services using SnapLogic Snowflake: Automated Continuous Azure Data Lake Storage Replication to Snowflake SQL Server: Automated Continuous Azure Data Lake Storage Replication to SQL Server SQL Server Linked Server: Connect to Azure Data Lake Storage Data as a SQL Server Linked Server SQLite: Automated Continuous Azure Data Lake Storage Replication to SQLite Talend: Connect to Azure Data Lake Storage and Transfer Data in Talend UiPath Studio: Create an RPA Flow that Connects to Azure Data Lake Storage in UiPath Studio Vertica: Automated Continuous Azure Data Lake Storage Replication to a Vertica Database

Workflow & Automation Tools



Connect to Azure Data Lake Storage from popular data migration, ESB, iPaaS, and BPM tools.

Our drivers and adapters provide straightforward access to Azure Data Lake Storage data from popular applications like BizTalk, MuleSoft, SQL SSIS, Microsoft Flow, Power Apps, Talend, and many more.

Popular Workflow & Automation Tool Integrations



Developer Tools & Technologies



The easiest way to integrate with Azure Data Lake Storage from anywhere. Our Azure Data Lake Storage drivers offer a data-centric model for Azure Data Lake Storage that dramatically simplifies integration — allowing developers to build higher quality applications, faster than ever before. Learn more about the benefits for developers:



Popular Developer Integrations



.NET Charts: DataBind Charts to Azure Data Lake Storage .NET QueryBuilder: Rapidly Develop Azure Data Lake Storage-Driven Apps with Active Query Builder Angular JS: Using AngularJS to Build Dynamic Web Pages with Azure Data Lake Storage Apache Spark: Work with Azure Data Lake Storage in Apache Spark Using SQL AppSheet: Create Azure Data Lake Storage-Connected Business Apps in AppSheet C++Builder: DataBind Controls to Azure Data Lake Storage Data in C++Builder ColdFusion: Query Azure Data Lake Storage in ColdFusion Using JDBC ColdFusion: Query Azure Data Lake Storage in ColdFusion Using ODBC Dash: Use Dash & Python to Build Web Apps on Azure Data Lake Storage Delphi: DataBind Controls to Azure Data Lake Storage Data in Delphi DevExpress: DataBind Azure Data Lake Storage to the DevExpress Data Grid EF - Code First: Access Azure Data Lake Storage with Entity Framework 6 EF - LINQ: LINQ to Azure Data Lake Storage EF - MVC: Build MVC Applications with Connectivity to Azure Data Lake Storage Filemaker Pro: Bidirectional Access to Azure Data Lake Storage from FileMaker Pro Filemaker Pro (on Mac): Bidirectional Access to Azure Data Lake Storage from FileMaker Pro (on Mac) Go: Write a Simple Go Application to work with Azure Data Lake Storage on Linux Google Apps Script: Connect to Azure Data Lake Storage Data in Google Apps Script Hibernate: Object-Relational Mapping (ORM) with Azure Data Lake Storage Entities in Java IntelliJ: Connect to Azure Data Lake Storage in IntelliJ JBoss: Connect to Azure Data Lake Storage from a Connection Pool in JBoss JDBI: Create a Data Access Object for Azure Data Lake Storage using JDBI JRuby: Connect to Azure Data Lake Storage in JRuby Microsoft Power Apps: Integrate Live Azure Data Lake Storage Data into Custom Business Apps Built in Power Apps NodeJS: Query Azure Data Lake Storage Data in Node.js (via Connect Server) NodeJS: Query Azure Data Lake Storage through ODBC in Node.js PHP: Access Azure Data Lake Storage in PHP through the Cloud Hub PHP: Natively Connect to Azure Data Lake Storage in PHP PowerBuilder: Connect to Azure Data Lake Storage from PowerBuilder PowerShell: Pipe Azure Data Lake Storage to CSV in PowerShell PyCharm: Using the CData ODBC Driver for Azure Data Lake Storage in PyCharm Python: Connect to Azure Data Lake Storage in Python on Linux/UNIX React: Build Dynamic React Apps with Azure Data Lake Storage Data Ruby: Connect to Azure Data Lake Storage in Ruby RunMyProcess: Connect to Azure Data Lake Storage Data in RunMyProcess RunMyProcess DSEC: Connect to Azure Data Lake Storage in DigitalSuite Studio through RunMyProcess DSEC SAP UI5: Integrate Real-Time Access to Azure Data Lake Storage in SAPUI5 MVC Apps Servoy: Build Azure Data Lake Storage-Connected Apps in Servoy Spring Boot: Access Live Azure Data Lake Storage Data in Spring Boot Apps SQLAlchemy: Use SQLAlchemy ORMs to Access Azure Data Lake Storage in Python Tomcat: Configure the CData JDBC Driver for Azure Data Lake Storage in a Connection Pool in Tomcat Unqork: Create Azure Data Lake Storage-Connected Applications in Unqork VCL App (RAD Studio): Build a Simple VCL Application for Azure Data Lake Storage WebLogic: Connect to Azure Data Lake Storage from a Connection Pool in WebLogic


When Only the Best Azure Data Lake Storage Drivers Will Do

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Frequently Asked Azure Data Lake Storage Driver Questions

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


The Azure Data Lake Storage driver acts like a bridge that facilitates communication between various applications and Azure Data Lake Storage, allowing the application to read data as if it were a relational database. The Azure Data Lake Storage driver abstracts the complexities of Azure Data Lake Storage APIs, authentication methods, and data types, making it simple for any application to connect to Azure Data Lake Storage data in real-time via standard SQL queries.

Working with a Azure Data Lake Storage Driver is different than connecting with Azure Data Lake Storage through other means. Azure Data Lake Storage API integrations require technical experience from a software developer or IT resources. Additionally, due to the constant evolution of APIs and services, once you build your integration you have to constantly maintain Azure Data Lake Storage integration code moving forward.

By comparison, our Azure Data Lake Storage Drivers offer codeless access to live Azure Data Lake Storage data for both technical and non-technical users alike. Any user can install our drivers and begin working with live Azure Data Lake Storage data from any client application. Because our drivers conform to standard data interfaces like ODBC, JDBC, ADO.NET etc. they offer a consistent, maintenance-free interface to Azure Data Lake Storage data. We manage all of the complexities of Azure Data Lake Storage integration within each driver and deploy updated drivers as systems evolve so your applications continue to run seamlessly.

Many organizations draw attention to their library of connectors. After all, data connectivity is a core capability needed for applications to maximize their business value. However, it is essential to understand exactly what you are getting when evaluating connectivity. Some vendors are happy to offer connectors that implement basic proof-of-concept level connectivity. These connectors may highlight the possibilities of working with Azure Data Lake Storage, but often only provide a fraction of capability. Finding real value from these connectors usually requires additional IT or development resources.

Unlike these POC-quality connectors, every CData Azure Data Lake Storage driver offers full-featured Azure Data Lake Storage data connectivity. The CData Azure Data Lake Storage drivers support extensive Azure Data Lake Storage integration, providing access to all of the Azure Data Lake Storage data and meta-data needed by enterprise integration or analytics projects. Each driver contains a powerful embedded SQL engine that offers applications easy and high-performance access to all Azure Data Lake Storage data. In addition, our drivers offer robust authentication and security capabilities, allowing users to connect securely across a wide range of enterprise configurations. Compare drivers and connectors to read more about some of the benefits of CData's driver connectivity.

With our drivers and connectors, every data source is essentially SQL-based. The CData Azure Data Lake Storage driver contains a full SQL-92 compliant engine that translates standard SQL queries into Azure Data Lake Storage API calls dynamically. Queries are parsed and optimized for each data source, pushing down as much of the request to Azure Data Lake Storage as possible. Any logic that can not be pushed to Azure Data Lake Storage is handled transparently client-side by the driver/connector engine. Ultimately, this means that Azure Data Lake Storage looks and acts exactly like a database to any client application or tool. Users can integrate live Azure Data Lake Storage connectivity with ANY software solution that can talk to a standard database.

The Azure Data Lake Storage drivers and connectors offer comprehensive access to Azure Data Lake Storage data. Our Azure Data Lake Storage driver exposes static and dynamic data and metadata, providing universal access to Azure Data Lake Storage data for any enterprise analytics or data mangement use. To explore the Azure Data Lake Storage driver data model, please review the edition-specific Azure Data Lake Storage driver documentation.

Using the CData Azure Data Lake Storage drivers and connectors, Azure Data Lake Storage can be easily integrated with almost any application. Any software or technology that can integrate with a database or connect with standards-based drivers like ODBC, JDBC, ADO.NET, etc., can use our drivers for live Azure Data Lake Storage data connectivity. Explore some of the more popular Azure Data Lake Storage data integrations online.

Azure Data Lake Storage Analytics is universally supported for BI and data science. In addition, CData provides native client connectors for popular analytics applications like Power BI, Tableau, and Excel that simplify Azure Data Lake Storage data integration. Additionally, native Python connectors are widely available for data science and data engineering projects that integrate seamlessly with popular tools like Pandas, SQLAlchemy, Dash, and Petl.

Azure Data Lake Storage data integration is typically enabled with CData Sync, a robust any-to-any data pipeline solution that is easy to set up, runs everywhere, and offers comprehensive enterprise-class features for data engineering. CData Sync makes it easy to replicate Azure Data Lake Storage data any database or data warehouse, and maintain parity between systems with automated incremental Azure Data Lake Storage replication. In addition, our Azure Data Lake Storage drivers and connectors can be easily embedded into a wide range of data integration tools to augment existing solutions.

Absolutely. CData offers native Excel Add-Ins for Azure Data Lake Storage integration. These Add-Ins provide live access to Azure Data Lake Storage data directly from Microsoft Excel.