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TigerGraph expands reach of its graph database technology

With demand for graph analytics on the rise, TigerGraph recently unveiled an expanded partner ecosystem that will enable the vendor to gain domain expertise as its userbase grows.

With demand for graph database technology on the rise, TigerGraph revealed an expanded partner ecosystem that the vendor said will enable it to increase its domain expertise as it works with a growing array of customers.

Graph databases enable customers to access data in different ways than traditional relational databases. While relational databases are able to connect data points to just one other data point at a time, graph databases enable data points to connect to multiple other data points at once -- speeding up, in many cases, the process of developing data sets that are used to eventually make data-driven decisions.

Gartner listed graph database technology among its top 10 data and analytics trends each of the past few years and, in 2019, predicted graph processing and graph database management systems would grow 100% annually through the end of 2022.

As evidence of the expanding interest in graph database technology and its expected growth, TigerGraph, a native graph database vendor founded in 2012 and based in Redwood City, Calif., raised $105 million Series C funding in February 2021 to bring its total funding to $170 million. Four months later, Neo4j, another graph database vendor, tripled that amount by raising $325 million in Series F funding to bring its total valuation to more than $2 billion.

At the time of TigerGraph's recent funding round, the vendor said it planned to use the infusion of capital to fund development of its graph database technology, expand into new markets and increase its staff and presence in already-established locations.

Its expanded partner ecosystem will help fuel that growth by giving TigerGraph expertise as it works with customers in an array of different industries, COO Todd Blaschka said in a release.

The graph model, for a lot of scenarios, is very attractive, both in terms of its performance and its flexibility.
Donald FarmerFounder and principal, TreeHive Strategy

Similarly, Donald Farmer, founder and principal at TreeHive Strategy, based in Woodinville, Wa., said TigerGraph's increased partner ecosystem will help the vendor grow.

"It enables them to scale," he said. "You can't cover all scenarios, can't hire enough people to sell and service all your products -- particularly when products have associated service offerings. It enables them to get into more verticals, get into more industries, and that's important for TigerGraph because they are very services-heavy."

Dell, Expero and Xilinx are among the companies now part of TigerGraph's partner ecosystem and, by working with them, TigerGraph has been able to help organizations detect and fight financial crime, according to the vendor.

For example, TigerGraph and Expero, a custom software developer headquartered in Houston, developed a toolkit together that combats money laundering with graph database technology and machine learning.

In addition, the partnership with Expero led to the development of a tool for Exact Sciences Corp., a provider of cancer screening and diagnostic tests based in Madison, Wisc., which uses graph analytics to reach doctors with targeted marketing materials regarding cancer detection options, according to TigerGraph.

Other partnerships have led to the development of tools using graph database technology to help a COVID-19-tracking initiative in Côte d'Ivoire (Ivory Coast) and advance efficiency in the property and casualty insurance industry, TigerGraph said.

The partnerships are not only beneficial for TigerGraph, but also for its partners that are able to take advantage of the vendor's graph database technology, Farmer noted. Relational databases have, essentially, reached the limits of their capabilities, while there are growth opportunities in graph, he continued.

"The graph model, for a lot of scenarios, is very attractive, both in terms of its performance and its flexibility," Farmer said. "We're seeing hardware vendors respond to that. They made a lot of money developing hardware for relational databases, and now it's time to do the same for graph."

Farmer, however, sounded one note of caution regarding TigerGraph's expanded partner ecosystem.

While the vendor has added partnerships with a wide variety of companies and developed services with those partners to assist customers in an array of industries, TigerGraph does not yet have partnerships with any BI vendors and is missing out on some opportunities.

Seattle-based Tableau Software, for example, represents an opportunity for TigerGraph, given that CRM giant Salesforce is Tableau's parent company, according to Farmer.

Because of graph's ability to connect with more than one data point at a time, it's able to quickly find relationships between data points that relational databases either miss or take far more time to discover. That makes graph databases ideal for CRM, where there are often multiple profiles for single customers due to nicknames and initials, and it's not often obvious who might be family relations of one another.

"Tableau being integrated into Salesforce provides some great graph use cases," Farmer said. "CRM is such a natural place for a graph database system to be effective."

Beyond the expansion of its partner ecosystem, since raising its Series C funding in February, TigerGraph added support for the Google Cloud Platform (GCP) and unveiled new connectors to both Snowflake and Tableau. Before adding support for GCP in April, TigerGraph already supported both AWS and Microsoft Azure.

And despite expressing a desire to see partnerships with BI vendors, Farmer said TigerGraph is making intelligent choices that will continue to foster growth.

"TigerGraph has been very smart about building the depth of technology that's needed for robust, high-performance enterprise scenarios on graph," Farmer said. "That's really what distinguishes them."

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