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TigerGraph unveils support for GCP, adds new connectors

Graph database vendor TigerGraph unveiled support for Google Cloud and new connectors to Snowflake and Tableau on April 21 during its virtual user conference.

TigerGraph unveiled support for the Google Cloud Platform and new connectors to Snowflake and Tableau that will enable customers to more quickly derive insights from their data.

The vendor, founded in 2012 and based in Redwood City, Calif., revealed the new capabilities on Wednesday during Graph + AI Summit, its virtual user conference.

TigerGraph is a native graph database vendor that offers TigerGraph DB for on-premises users and TigerGraph Cloud, a graph database as a service, for customers who store their data in the cloud.

Graph databases enable users to access data in different ways than traditional relational databases do by connecting to multiple data points simultaneously rather than just one at a time, thus speeding up the process of developing data sets used to drive the decision-making process.

The new support for Google Cloud joins TigerGraph's support for Amazon Web Services and Microsoft Azure.

With the new support for Google Cloud, joint customers of TigerGraph and Google Cloud can use TigerGraph to take over all database management responsibilities, enabling analytics teams at organizations to focus on data science and analysis. All upgrades will be installed by TigerGraph, as will the administration and any service agreements related to their cloud data storage.

"Across the board, customers are asking if we can add support [so] they don't have to manage their data administration and they can focus on data science while we handle the upkeep, the upgrades and everything else," said Gaurav Deshpande, vice president of marketing at TigerGraph. "We're seeing this for large customers and small and midsize customers as well."

A no-code visual query is displayed on a sample screenshot from TigerGraph.
A sample screenshot from TigerGraph shows a no-code visual query under development.

Adding support for Google Cloud -- in addition to AWS and Azure -- meanwhile, is a positive development for TigerGraph, said Doug Henschen, principal analyst at Constellation Research.

"It's possible for customers to run software on any cloud, but it makes life easier if the vendor makes the software available as a service, as TigerGraph has done on AWS, Azure and now Google Cloud Platform," he said. "Standing up a service on each new cloud is not easy, but it's an investment in giving customers flexibility and choice."

The Snowflake connector, meanwhile, will enable joint TigerGraph and Snowflake customers to upload data from Snowflake to TigerGraph where they can explore, manipulate and analyze data before returning it to Snowflake.

Similarly, the Tableau connector will enable joint Tableau and TigerGraph customers to easily pull data from TigerGraph into Tableau for visualization and then send it back to TigerGraph when they're done with their analysis.

Both connectors, like the new support for Google Cloud, were developed in response to requests from customers, according to TigerGraph.

It makes life easier if the vendor makes the software available as a service, as TigerGraph has done on AWS, Azure and now Google Cloud Platform. Standing up a service on each new cloud is not easy, but it's an investment in giving customers flexibility and choice.
Doug HenschenPrincipal analyst, Constellation Research

"They wanted to do more advanced queries and ask complex questions, and they are too slow without TigerGraph," Deshpande said. "They're asking complex questions that go beyond one or two levels ... and we want them to be able to get answers to those complex questions with ease."

Supply chains, for example, have four levels -- with orders, features, parts and suppliers, he added.

With support now for each of the three major clouds and the addition of new connectors, TigerGraph next plans to continue working to improve its machine learning and data science capabilities, Deshpande said.

The vendor offers a host of prebuilt machine learning and data science algorithms for scenarios such as fraud detection, cybersecurity and recommendation engines, and is working to add more of those prebuilt tools.

"Customers have been asking for more graph-based algorithms out of the box," Deshpande said. "We already have a lot, but we want to expand those, especially around machine learning. You will see that as a major focus."

That focus, meanwhile, is key for TigerGraph as it continues to expand the array of services and capabilities it can offer customers, according to Henschen. The prebuilt algorithms are written by TigerGraph in GSQL, its graph query language, but are open source and can be modified by customers to fit their specific needs.

"In my view, the most notable thing that TigerGraph is doing is adding built-in support for machine learning and AI by way of prebuilt algorithms," he said. "This sort of in-database analysis can be a real time and money saver."

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