CData emerges as a data connectivity platform — without the platform

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With the explosion of data from today’s increasingly complex systems, the issue of data connectivity becomes more important than ever. CData, which has grown as a provider of drivers for data connectivity, is positioned for growth as a data connectivity platform — just without the platform. Instead, CData is focused on bringing data connectivity capabilities natively into the tools organizations already use, freeing companies and their already-taxed IT teams from the burden of implementing another full-bore integration platform.
Adding a data connectivity layer onto the hundreds of enterprise databases, applications, and platforms that organizations rely upon requires standards for connectivity. That’s the heart of CData’s growth. All of CData’s connectivity tools are built on the foundation of universally understood data standards, such as JDBC, ODBC, and ADO.NET.
CData provides a common SQL-based interface around the APIs offered by more than 200 SaaS/Cloud, application and database sources. “Having these driver interfaces allows us to bolt onto any application, including many existing cloud providers,” explained Eric Madariaga, chief marketing officer at CData. “Essentially, you’re able to add that connectivity without needing a large software product to run.”
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One of the benefits of standards-based connectivity is that it frees you from the constraints of application providers. Madariaga explained that if, for example, you’re using Marketo in your business, you don’t have to find the ETL tool that supports Marketo to move data in a warehousing scenario. “Any tool that supports database connectivity now can plug in our drivers and have access to that data source,” he said.
Beyond real-time integration, organizations are continuing to rely on data warehousing and ETL/ELT processes to support BI and Analytics.  CData supports these use cases through a combination of point data pipeline solutions like CData Sync, and the ability to extend connectivity for hyperscale cloud platforms through their standards-based drivers.
“Our pipeline, CData Sync, supports both the traditional ETL data movement and, more commonly, the ELT side,” Madariaga said. “Instead of doing complex transformation in moving data from source to destination, our customers just bulk-load everything to the destination and then do the transformation with the data warehouse engine. The ability to support those scenarios creates limitations on the types of destinations you can support. If you don’t do any kind of transformation on data, it’s very hard to support databases.
“For example, if you don’t have transformation capability, supporting SQL Server is going to be a problem,” he continued. “You might be able to create the table the first time. You can get everything into your data table and it will start pumping data in there, but if the schema changes on the other side, your process breaks. You have to re-engineer the whole process because you haven’t been able to recast the schema inside the database to support what you have on the other side. Today, you need those kinds of transformation capabilities. Our ETL product supports those.”
Madariaga said CData is looking to align more with broader cloud service providers to support ETL and ELT for them in a broader context, without the need for an additional transformation tool.
The same thing holds true with the big three cloud ETL platform providers, which can use CData’s drivers to extend their cloud ETL data-movement products. From AWS Glue’s managed ETL service connected to CData, for example, users can connect to the more than 200 different data sources to which CData provides access, without having to go to a specific third-party ETL product. “It’s all based on use-case,” Madariaga pointed out. “We don’t want to be prescriptive in how the customer works with data; we just want to make sure they can use the tools they already have to work with the data they want.”
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