Spark Drivers & Connectors
for Data Integration

Connect to live Apache Spark from BI, analytics, and reporting tools through bi-directional data drivers. Maps SQL to Spark SQL Easily integrate Spark 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 Spark data with BI, analytics, reporting and data visualization technologies. They provide unmatched query performance, comprehensive access to Spark 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 Spark in Alteryx Designer (ODBC) Alteryx Designer: Work with Live Spark Data in Alteryx Designer (Connect Cloud) Amazon QuickSight: Build Interactive Dashboards from Spark Data in Amazon QuickSight Amazon SageMaker: Integrate Live Spark data into Amazon SageMaker Canvas Aqua Data Studio: Connect to Spark in Aqua Data Studio AWS Databricks: Process & Analyze Spark Data in Databricks (AWS) Azure Analysis Services: Model Spark Data Using Azure Analysis Services Birst: Build Visualizations of Spark in Birst BIRT: Design BIRT Reports on Spark Clear Analytics: Build Charts with Spark in Clear Analytics Cognos Analytics (On-Prem): Analyze Spark Data in Cognos Analytics DBxtra: Build Dashboards with Spark in DBxtra Domo: Create Datasets from Spark in Domo Workbench Dundas BI: Build Dashboards with Spark in Dundas BI Excel (on Mac OS): Work with Spark Data in MS Excel on Mac OS X FineReport: Feed Spark into FineReport Google Sheets: Access Live Spark Data in Google Sheets IBM Cognos BI: Create Data Visualizations in Cognos BI with Spark Infragistics Reveal: Analyze Spark Data in Infragistics Reval JasperServer: Create Spark Reports on JasperReports Server Jaspersoft BI Suite: Connect to Spark in Jaspersoft Studio JReport Designer: Integrate with Spark in JReport Designer Klipfolio: Create Spark-Connected Visualizations in Klipfolio KNIME: Enable the Spark JDBC Driver in KNIME LINQPad: Working with Spark in LINQPad Looker: Analyze Spark Data in Looker Looker Studio: Create Reports from Spark Data in Looker Studio Metabase: Create Interactive Spark-Connected Metabase Dashboards Microsoft Excel: Access Live Spark Data in Excel Desktop Microsoft Excel for the Web: Access Live Spark Data in Excel for the Web Microsoft SSAS: Build an OLAP Cube in SSAS from Spark MicroStrategy: Connect to Live Spark Data in MicroStrategy through Connect Cloud MicroStrategy: Use the CData JDBC Driver for Spark in MicroStrategy Microstrategy Desktop: Use the CData JDBC Driver for Spark in MicroStrategy Desktop Microstrategy Web: Use the CData JDBC Driver for Spark in MicroStrategy Web Mode Analytics: Create Spark-Connected Visualizations in Mode OBIEE: Spark Reporting in OBIEE with the Spark JDBC Driver pandas: Use pandas to Visualize Spark in Python Pentaho Report Designer: Integrate Spark in the Pentaho Report Designer Power BI Desktop: Author Power BI Reports on Real-Time Spark Power BI Service: Visualize Live Spark Data in the Power BI Service Power Pivot: Access Spark Data in Microsoft Power Pivot Power Query: Access Spark Data in Microsoft Power Query Qlik Cloud: Create Apps from Spark Data in Qlik Sense Cloud QlikView: Connect to and Query Spark in QlikView over ODBC R: Analyze Spark in R (JDBC) R: Analyze Spark in R (ODBC) RapidMiner: Connect to Spark in RapidMiner Redash: Build Spark-Connected Dashboards in Redash SAP Analytics Cloud: Analyze Spark Data in SAP Analytics Cloud SAP Business Objects: Create an SAP BusinessObjects Universe on the CData JDBC Driver for Spark SAP Crystal Reports: Publish Reports with Spark in Crystal Reports SAS: Use the CData ODBC Driver for Spark in SAS for Real-Time Reporting and Analytics SAS JMP: Use the CData ODBC Driver for Spark in SAS JMP SAS Viya: Analyze Live Spark Data in SAS Viya Sisense: Visualize Live Spark in Sisense Spago BI: Connect to Spark in SpagoBI Tableau: Visualize Spark in Tableau Desktop Tableau Cloud: Build Spark Visualizations in Tableau Cloud Tableau Server: Publish Spark-Connected Dashboards in Tableau Server TIBCO Spotfire: Visualize Spark in TIBCO Spotfire through ADO.NET TIBCO Spotfire: Visualize Spark Data in TIBCO Spotfire TIBCO Spotfire Server: Operational Reporting on Spark from Spotfire Server Visio: Link Visio Shapes to Spark Zoho Analytics: Create Spark-Connected Dashboards in Zoho Analytics

ETL, Replication, & Warehousing

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

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

Popular Data Warehousing Integrations

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

Workflow & Automation Tools

Connect to Spark from popular data migration, ESB, iPaaS, and BPM tools.

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

When Only the Best Spark Drivers Will Do

See what customers have to say about our products and support.

Frequently Asked Spark Driver Questions

Learn more about Spark drivers & connectors for data and analytics integration

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

Working with a Spark Driver is different than connecting with Spark through other means. Spark 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 Spark integration code moving forward.

By comparison, our Spark Drivers offer codeless access to live Spark data for both technical and non-technical users alike. Any user can install our drivers and begin working with live Spark 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 Spark data. We manage all of the complexities of Spark integration within each driver and deploy updated drivers as systems evolve so your applications continue to run seamlessly.

If you need truly zero-maintenance integration, check out connectivity to Spark via CData Connect Cloud. With Connect Cloud you can configure all of your data connectivity in one place and connect to Spark from any of the available Cloud Drivers and Client Applications. Connectivity to Spark is managed in the cloud, and you never have to worry about installing new drivers when Spark is updated.

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 Spark, 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 Spark driver offers full-featured Spark data connectivity. The CData Spark drivers support extensive Spark integration, providing access to all of the Spark 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 Spark 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 Spark driver contains a full SQL-92 compliant engine that translates standard SQL queries into Spark API calls dynamically. Queries are parsed and optimized for each data source, pushing down as much of the request to Spark as possible. Any logic that can not be pushed to Spark is handled transparently client-side by the driver/connector engine. Ultimately, this means that Spark looks and acts exactly like a database to any client application or tool. Users can integrate live Spark connectivity with ANY software solution that can talk to a standard database.

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

Using the CData Spark drivers and connectors, Spark 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 Spark data connectivity. Explore some of the more popular Spark data integrations online.

Additionally, since Spark supported by CData Connect Cloud, we enable all kinds of new Spark cloud integrations.

Spark Analytics and Spark Cloud BI integration 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 Spark 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.

Spark 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 Spark data any database or data warehouse, and maintain parity between systems with automated incremental Spark replication. In addition, our Spark drivers and connectors can be easily embedded into a wide range of data integration tools to augment existing solutions.

Absolutely. The best way to integrate Spark with Excel is by using the CData Connect Cloud Excel Add-In. The Spark Excel Add-In provides easy Spark integration directly from Microsoft Excel Desktop, Mac, or Web (Excel 365). Simply configure your connection to Spark from the easy-to-use cloud interface, and access Spark just like you would another native Excel data source.