Esri marries GIS and graph data

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Developer kits connecting Esri geospatial data with photorealistic renderings in Unreal and Unity gaming engines took center stage at Esri’s Developer Conference 2022 in Palm Springs, California last week. Such tooling is an important step forward for the metaverse.

However, details about a new backend offering also sparked interest. At the event, the company coupled its flagship ArcGis Pro geographic information system with a chart analysis user interface, chart server and chart data store. The offering is called ArcGIS Knowledge.

The NoSQL-style graphical data technologies, often integrated by application specialists such as Esri, represent a new take on analytics that is gaining traction.

Unlike table-based relational database management systems (RDBMSs), graph systems contain data in collections of entities or nodes – they are connected by edges that describe the relationship between them. Ironically, at least in some cases, the graphical data system handles relationships better than the relational system.

The graph data models appear in edge-and-node maps that are less like the nested tables of enterprise RDBMS schemas and more like the corkboard investigation maps of TV crime shows.

Pay attention to the graph

Graph analysis is an entirely new area for GIS, according to Esri founder and president Jack Dangermond, with the potential to advance several new types of data discovery as graph technology informs geographic applications, which is a must-have in many big data projects.

“It allows us to create linkage diagrams and perform powerful analytics across a range of applications, such as supply chain analytics, disease tracking, and crime analysis,” he told an Esri software conference focused on government apps last month. He said graph analysis’s ability to show how people and things are related will significantly improve the processing of spatial data.

In fact, ArcGIS Knowledge “brings together the world of graph data and geospatial data,” Sud Menon, director of software development at Esri, told attendees at the Palm Springs conference. “The synergy is very powerful. There is a lot of insight that can be gained by analyzing these in context,” he said.

As described at the event, ArcGIS Knowledge supports queries via a version of the openCypher Query language that it has extended for spatial use. That suggests developers looking to create their own queries could tap into skills that are useful to other graph engines.

Shifts in Graph Data Delivery

To date, the graph data cause has advanced based on efforts by native grave database creators such as ArangoDB, Cambridge Semantics, Neo4j, TigerGraph and others, with Neo4j being a particularly notable advocate. Established database players such as AWS, IBM, Microsoft, and Oracle offer native graph databases or graph analytics that run on relational engines.

According to Emergen Research, the global chart database market size reached $1.59 billion in 2020 and is expected to register a revenue CAGR of 21.9% through 2028. Gartner estimates that by 2025, chart technologies will be used in 80% of the data and analytics innovations, by 10% in 2021.

Graph capabilities are increasingly taking the form of embedded systems used as part of a larger system. This applies to master data management (MDM) applications offered by, for example, Informatica and Reltio for master data management. The chart stores underlie the fraud detection offerings and the geographic supply chain apps spotted by Esri.

As emerging graphics database vendors go straight to the enterprise, there could be a greater shift in the future as ISVs and others design graphics technologies within applications.

Chart data conforms to GIS maps

According to Jean Villedieu, co-founder and director of Linkurious, connecting graphical representations of data with geographic data has special value in many applications.

The company is a major player in the graphical analytics ecosystem, with a focus on financial crime detection and investigation solutions. Linkurious counts Deloitte, Capgemini and PWC, Neo4j, RedisLabs and others as partners.

“We see people mixing chart and map data to understand context and gain insights,” Villedieu told VentureBeat. He added that security and fraud detection can especially benefit from such data integrations, as geographic proximity can be a very telling data point.

The company’s skills, along with those of graphics database creator Neo4j, took center stage as the software was applied in widespread “Panama Papers” studies. Led by the International Investigative Journalist Consortium, the Panama Papers uncovered secret offshore accounts hiding the wealth of world leaders and their associates.

Linkurious sees a mix of customers these days, with the majority coming from direct sales to customers. But partners, including ISVs, are a growing part of the business, Villedieu said. “The next wave will be more about applications embedding these graphics technologies into new products.”

Specialist Requirements

While one analyst agreed that graphical databases exhibit market dynamics, he cautioned that adherents of established relational methods can adapt to the most common use cases.

“There are quite a few chart analysis that can be performed by non-graph platforms,” said Philip Howard, research director for information management at Bloor Research. “However, there are some graphics algorithms that absolutely require a graphics database.”

The best applications of Graph databases, he said, appear where query processing in complex networks of relationships is vital. He mentions MDM, transport logistics and data line as examples. Howard describes these as ‘specialist requirements’.

“Outside these areas, you don’t really need a chart database. This will limit adoption,” Howard said.

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