Spinning up Cloud-scale Analytics is now Even More Compelling with Talend and Microsoft

Today, we’re excited to share two announcements that make adopting Microsoft Azure SQL Data Warehouse (ADW) a no-brainer.

First, ADW significantly increased the lead over the competition with the new price-performance benchmarks published by GigaOm, showing exponential price-performance improvements over similar solutions. This should be especially interesting to large enterprises with legacy, on-premises data warehouse deployments that can benefit from the best-in-class performance, security, and unmatched cost advantages of Azure SQL Data Warehouse.

Second, Stitch Data Loader, our recent addition to help support our small and mid-market customers, now supports Microsoft Azure SQL Data Warehouse destinations. With Stitch Data Loader, customers can load 5 million rows/month into Azure SQL Data Warehouse for free, or scale up to an unlimited amount of rows with a subscription.

All across the industry, there is a rapid shift to the cloud. Utilizing fast, flexible, and secure cloud data warehouse is an important first step in that journey. With Microsoft Azure SQL Data Warehouse and Stitch Data Loader companies can get started faster than ever. The fact that ADW can be up to 14x faster, and 94% less expensive than similar options in the marketplace, should only help further accelerate adoption of cloud scale analytics by customers of all sizes.

An intro to Microsoft Azure SQL Data Warehouse

Azure SQL Data Warehouse is a fully managed cloud data warehouse for enterprises of any size that combines lightning-fast query performance with industry-leading data security. With ADW, users are billed for compute and storage resources independently. You can increase storage when you need to without being forced to increase compute capacity simultaneously, so you pay for only what you need.

Azure SQL Data Warehouse’s elastic scalability also makes it fast and cost-effective to scale compute and storage resources with latency measured in seconds or minutes. That means you no longer have to perform the preload transformations required with ETL. Instead, you can load all of your raw data into your data warehouse, then define transformations in SQL and run them in the data warehouse at query time. This new sequence has changed ETL into ELT.

Building pipelines to the cloud with Stitch Data Loader

The Stitch team built the Azure SQL Data Warehouse integration with the help of Microsoft engineers. The solution leverages Azure Blob Storage and PolyBase to get data into the Azure cloud and ultimately loaded to SQL Data Warehouse. We take care of all issues with data type transformation between source and destination, schema changes, and bulk loading.

To start moving data, just specify your host address and database name and provide authentication credentials. Stitch will then start loading data from all of your sources in minutes.

Stitch Data Loader enables Azure SQL Data Warehouse users to analyze data from more than 90 data sources, including databases, SaaS tools, and ad networks. We also sponsor and integrate with the Singer open source ETL project, which makes it easy to get additional or custom data sources into Azure SQL Data Warehouse.

Stitch’s destination switching feature also makes it easy for existing Stitch users to take their existing integrations and start loading them into Azure SQL Data Warehouse right away.

Going further with Talend Cloud and Azure SQL Data Warehouse

What if you’re ready to scale out your data warehousing efforts and layer on data transformation, profiling, and quality? Talend Cloud offers many more sources as well as more advanced data processing and data quality features that are available within the ADW and the Azure Platform. With over 900 connectors available, you’ll be able to move all your data, no matter the format or source. With data preparation and additional security features built-in, you can get Azure-ready in no time.

Take Uniper for instance. Using Azure and Talend Cloud, they built a cloud-based data analytics platform to integrate over 100 data sources including temperature and IoT sensors, from various external and internal sources. They constructed the full flow of business transactions — spanning market analytics, trading, asset management, and post-trading — while enabling data governance and self-service, resulting in reduced integration costs by 80% and achieving ROI in 6 months.

What next?

Learn more about how you can use Stitch and Azure SQL Data Warehouse to build your data analytics stack.

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