HDFS drivers & connectors for data integration

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

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

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

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

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

HDFS 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 HDFS 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.

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