Parquet Drivers & Connectors
for Data Integration

Connect to Parquet columnar storage from BI, analytics, and reporting tools through standards-based drivers. Easily integrate Parquet data with BI, Reporting, Analytics, ETL Tools, and Custom Solutions.

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Other Technologies

BI & Analytics

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

ETL, Replication, & Warehousing

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

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

Workflow & Automation Tools

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

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

When Only the Best Parquet Drivers Will Do

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

Frequently Asked Parquet Driver Questions

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

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

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

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

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

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

Parquet 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 Parquet 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.

Parquet 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 Parquet data any database or data warehouse, and maintain parity between systems with automated incremental Parquet replication. In addition, our Parquet 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 Parquet integration. These Add-Ins provide live access to Parquet data directly from Microsoft Excel.