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The Trovares Connector:

For Neo4j, Oracle, Snowflake, MongoDB, SAP, MySQL, PostgreSQL, AuroDB, & Databricks

Turbocharge your analytics with xGT.

Time to insights for graph query results is key! Finding the bad actors, powering workflows, managing supply chain risks, waiting for the relevant data to power business workflows, empowering managerial oversight with reports and advanced analytics, and more – all depend upon quickly getting the results. Trovares can easily leverage your existing investment in Neo4j with our database-independent, high-performance, patented Graph Analytics software.

Lightning-fast ingest and query speed.
Why does this matter? 

Sure Trovares xGT is faster than Neo4j and others, but why does that matter to me? There are endless use cases where ingest speed and query time are vitally important, especially in cases where the data analysis has a time limit (cyber, shipping and hauling, etc.) and a new set of data is coming in right after. It can even be essential when working with a large amount of static data, as Neo4j will “Hit a wall.”

Below are some (but not all) example industries and use cases where Trovares xGT thrives.

Fraud Detection

Large telecom companies with e-mail services deal with bad actors trying to use their services to commit fraud. These bad actors are intelligent and have crafty ways to get around most systems. The only way to solve a problem like this is to look at the entire data set (very massive in most cases) and run queries to discover fraudulent activity. This is somewhere where sharding the graph could be detrimental to the result. Most of the loopholes bad actors use rely on taking advantage of the data being separated.

Deep Graph Search

Graph Search can be a simple “lookup,” or it can be a deeper search.  Lookups are measured in transactions per second.  These are automated applications like checking a credit card number.  Intuitive analytical queries are measured by their response time in human time, measured in seconds, minutes, and hours. Analysts need a response before they forget the question.  Then, they often wish to ask a follow-up question.  A search engine, Trovares xGT that can provide answers in seconds when querying a 300-billion edge graph is a necessary tool for the serious data scientist.

Digital Forensics 

In this case, a bad actor penetrated your network and has been resident in your network for longer than you realize. Cyber intruders are known to wait months or longer to carry out their plans. Financial institutions face the risk of immense loss from cyber-attacks, they must carry a large reserve of cash (negative for the bottom line) to hedge against such risk. Proof that an Enterprise has invested in digital forensic searches to minimize the risk that their networks have been penetrated results in savings for the reserve (positive for the bottom line).   


Advertising has changed before our eyes in the last decade. Market research and available statistics previously allowed corporations to discover a population's preferences. Now, with the recent explosion of individual consumer data, we can see the preferences of specific people. This problem could be small for a mom-and-pop retailer, but for a giant corporation, it becomes massive very quickly. Not only is it essential to retain all the information of specific people, but fast analysis is necessary to deliver the right advertisements to the right people.

Shipping & Handling 

With so many moving parts in a shipping pipeline, some companies juggle massive amounts of data. With so much information to keep track of, such as Retailers, customers, planes, boats, trucks, their handlers, crates, and even loading machinery, many enterprises are dropping the ball along the way. Leading to full crates in the port and long lines of truckers waiting hours for shipments. We offer a dynamic graph solution to manage the data and run analytics to find the weak points of the pipeline.


Many large-scale problems need solving in the Biotech field. Among the many are genomics and genome representation, neural networks, pharmaceutical research, and more. These are all problems that translate to graphs perfectly. 

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