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The Denodo Platform meets BigQuery

It’s only natural that the Denodo Platform would achieve theGoogle Cloud Ready – BigQuery designation earlier this month; after all, the Denodo Platform and Google BigQuery have much in common.

The Denodo Platform, powered bydata virtualization, enables real-time access across disparate on-premises and cloud data sources, without replication, andBigQuery, the cloud-based enterprise data warehouse (EDW) on Google Cloud , enables blazing-fast query-response across petabytes of data, even when some of that data is stored outside of BigQuery in on-premises systems.

For users of the Denodo Platform on Google Cloud, BigQuery certification offers confidence that the Denodo Platform’s data integration and data management capabilities work seamlessly with BigQuery, as Google only confers this designation on technology that meets stringent functional and interoperability requirements.

In addition to storage “elbow room,” BigQuery brings new analytical capabilities to Denodo Platform users on Google Cloud, including out-of-the box machine learning (ML) capabilities like Apache Zeppelin for Denodo, as well as geospatial, business intelligence (BI), and other types of data analysis tools.

But it gets better.

The Denodo Platform on Google Cloud + BigQuery

Combining the full power of the Denodo Platform with BigQuery enables easy access to a wider breadth of data, all with a single tool. The Denodo Platform’s ability to deliver data in real time over BigQuery cloud-native APIs enables frictionless data movement between on-premises, cloud, and Google Cloud Storage data sources.

Enhanced BigQuery support combines Google’s native connectivity with the Denodo Platform’s query pushdown optimization features, to process massive big-data workloads with better performance and efficiency. For further performance, BigQuery can be leveraged as a high-performance caching database for the Denodo Platform in the cloud. This supports advanced optimization techniques like multi-pass executions based on intermediate temporary tables.

Users also benefit from the same flexible pricing available on Google Cloud, letting them start small with BigQuery, and scale as needed.

Use Cases Abound

Combining the Denodo Platform with BigQuery enables a wide variety of use cases, such as:

Machine Learning/Artificial Intelligence (ML/AI) and Data Science in the Cloud

Users can leverage the Denodo Platform’s data catalog to search the available datasets and tag the right ones for analytics and ML projects. This also helps data scientists to combine data stored in BigQuery and data virtualization layers to build models in a quick and easy manner, putting cloud elasticity to work. Using the metadata and data lineage capabilities of the Denodo Platform, users can access all of the data in a governed fashion.

Zero-Downtime Migrations and Modernizations

The Denodo Platform acts as a common access point between two or more data sources, providing access to multiple sources, simultaneously, even when the sources are moved, while hiding the complexities of access from the data consumers. This enables seamless, zero-downtime migrations from on-premises systems or other cloud data warehouses (such as Oracle or SQL Server) to BigQuery. Similarly, the Denodo Platform makes it possible for stakeholders to modernize their systems, in this case their BigQuery instance, with zero impact on users.

Data Lake Creation 

Users can easily create virtual data lakes, which combine data across sources, regardless of type or location, while also enabling the definition of a common semantic model across all of the disparate sources.

Data-as-a-Service (DaaS) 

The Denodo Platform also facilitates easy delivery of BigQuery and Google Cloud Storage data (structured and semi-structured) to users as an API endpoint. With this support, the platform lets companies expose data in a controlled, curated manner, delivering only the data that is suitable for specific business partners and other external companies, and easily monetizing relevant datasets when needed.

The Dream of a Hybrid Data Warehouse, Realized

Let’s look at one way that the Denodo Platform and BigQuery can work together on Google Cloud. In the architecture illustrated below, the two technologies enable a hybrid (on-premises/cloud) data warehouse configuration.

I’d like to point out a few things in this diagram (see the numbered circles). You can:

Move your relational data for interactive querying and offline analytics to BigQuery.

Move your relational data from large scale databases and applications to Google Spanner, when you need high I/O and global consistency.

Move your relational data from Web frameworks and existing applications to Google Cloud SQL.

Combine all of these sources with the relational data sitting on-premises in a traditional data warehouse, creating a single centralized data hub.

Run real-time queries on virtual data from other applications.

Build operational reports and analytical dashboards on top of the Denodo Platform to gain insights from the data, and use Looker or other BI tools to serve thousands of end users.

Getting Started

BigQuery certification provides Denodo Platform users on Google Cloud with yet another reason to appreciate Google Cloud. Visit the Denodo Platform for Google Cloud page for more information.

If you are new to the Denodo Platform on Google Cloud, there is no better way to discover its power than to try it out for yourself. Denodo offers not only a way to do that, for free for 30 days, but also built-in guidance and support.

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