Panoply Gives Customers More Storage and Higher Performance with Move to Google Cloud BigQuery for Data Warehousing

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Panoply Gives Customers More Storage and Higher Performance with Move to Google Cloud BigQuery for Data Warehousing

June 15
18:21 2021
New data warehouse compatibility gives customers a larger data repository for greater data agility with faster performance to connect to BI tools that grow with their business.

San Francisco, CA, USA – June 15, 2021 – Panoply, a cloud data platform that makes it easy to sync, store, and access business data, today announced that the company is now hosting its data warehouse services on Google Cloud BigQuery. Panoply users can now link data from a variety of sources to any business intelligence tool compatible with BigQuery, including Looker, Tableau, Power BI, and Google Data Studio to simplify analytics and set up or improve their data stack from end to end.

All Panoply users still have access to the same, easy-to-use data sources, only now they have more data warehouse space and improved ingestion performance with greater cost efficiency. With the move to BigQuery, every Panoply user receives at least 1 TB of data storage, an unlimited number of data connections, and high-quality customer support from Panoply’s team of data experts.

“BigQuery is gaining popularity because of its power and flexibility,” says Paul Friesen, CEO of Panoply. “By moving our data storage services to BigQuery we can offer Panoply customers a data warehouse platform that offers more capacity, speed, and scalability so their analytics and business intelligence tools can grow with their business.”

In addition to providing customers with ample storage, the move to BigQuery allows Panoply to separate storage and compute, offering the benefit of data scalability to users while using Google Cloud’s data repository. Users only pay for what they need, and separating the data store from computer processing makes it easier for users to scale as their business grows. BigQuery offers excellent data caching to speed up repeated queries and also delivers better performance since there is no limit on the computing power applied, making the solution better suited for large data sets. Users also have access to Google Data Studio, the free interactive dashboard and visualization tool.

“We are delighted that Panoply is migrating to BigQuery. Panoply has been a key player in the cloud for years, and now our two organizations can collaborate to accelerate data practitioners’ time to insight,” said Sudhir Hasbe, senior director, product management, Google Cloud. “In today’s fast-paced business environment, a reliable and agile data platform is essential. With BigQuery, Panoply’s customers gain power, scale, and speed, to more easily access critical business insights and maintain their competitive edge.”

With the move to BigQuery, Panoply has adjusted its fee structure as well. Plans start with 1 TB of data storage, and fees are based on the number of rows successfully scanned from connected data sources. Users only pay for the rows ingested into Panoply making fees easy to track, and the count is reset each month. Fees also are determined by the number of query bytes processed rounded to the nearest 10 MB. Query bytes are the units Google uses to track computing power against data stored in the data warehouse.

Find out more details about Panoply on BigQuery in their announcement here.

About Panoply

Founded in 2015, Panoply offers data warehousing and code-free data integration that helps businesses unlock business intelligence without the pain of complex pipeline management or time-consuming data warehouse configuration. The company’s best-in-class data analytics automates ETL processes and data warehouse setup to simplify the discovery of crucial insights that drive business growth. Panoply’s no-code integrations make it easy to connect data sources such as MySQL, Postgres, MongoDB, HubSpot, Salesforce, Shopify, Zendesk, and Google Analytics, as well an array of BI and analytics tools, enabling analysis in minutes without development overhead.

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