Graphical Analysis for Users: No Code Data Migration, Visual Query, and Free COVID-19 Analysis by TigerGraph
As we have been keep track of the graphics scene for quite some time now a couple of things have started to become apparent. One, the graph is here to stay. Second, there is still some way to go to make the benefits of databases and graphical analysis widely available and accessible. Add to that a new opportunity, because Harnessing Connections is where this technology shines, and you have the backdrop for today’s announcement by TigerGraph.
The graph is here to stay
Even though graphics databases have a history stretching back at least 20 years, it wasn’t until the last couple of years that they started to be in the limelight. The realization that the way data points are connected can deliver more information and value than the sheer volume of data seems to have touched. At the same time, graph technology has advanced, while the limitations of existing relational databases when it comes to exploiting connections are now well understood.
This has led to a perfect storm for graphics databases. Graphical databases went from a niche market to the fastest growing segment of data management in no time. Gartner, for example, predicted last year that this space will experience an annual growth compound of 100% year on year until 2022. Every industry executive we’ve spoken to seems to verify this – 2019 has been a really great year.
TigerGraph is no exception. TigerGraph is a newcomer to this space, having emerged from stealth in 2017. Prior to that, however, the folks at TigerGraph had been working on their platform since 2012. It’s starting to pay off, according to TigerGraph VP Marketing Gaurav Deshpande.
TigerGraph was one of the first graphics database vendors to announce a fully managed cloud service in late 2019. On a call with ZDNetDeshpande noted that while the cloud-based version of the platform has generally only been available for a while, it is seeing rapid adoption.
In the past four months alone, notes TigerGraph, more than 1,000 developers have harnessed the power of the graph to build applications on TigerGraph Cloud, the company’s graph-as-a-service database. This seems to be in line with the general trend: data, databases, and users all move to the cloud.
Yet, this is only one piece of the puzzle that graphics database vendors will need to solve. Being offered in the cloud can take care of the availability part, but what about accessibility? Not everyone is a graphics expert to start with. Even for those that are, it would help to have some sort of equivalent for the well-established technology stack that comes with relational databases in place.
Wide availability and accessibility: Cloud, no code, visual tools
That’s where TigerGraph’s announcement comes in. The first part of what TigerGraph dubs version 3.0 of its platform does not seem particularly revolutionary, but there is a feeling that it will be appreciated by many: the ability to automatically migrate data from relational databases to TigerGraph, without the need to build a data pipeline or create and map to a new graphical schema.
As seen in a demo released by TigerGraph, the migration does indeed seem quite painless. Deshpande commented that this is a feature that TigerGraph has been working on for some time, and that the time has finally come to release it. Early customer feedback has also been fairly positive.
While TigerGraph is not the only graph database vendor to offer a way to import data, other options often require an intermediate step, i.e. exporting to CSV format. This adds complexity and cost to the process, unlike what appears to be a fairly smooth import process for TigerGraph 3.0.
The flip side, however, is a lack of transparency and control. At this point, users have no way of controlling the process. This means that the built-in rules for mapping and schema creation apply. This can be more problematic than it sounds, especially for complex areas.
Clarity of perception and navigation, as well as query performance, are very dependent on an appropriate graphical data model. Depending on your field, a ready-made graphical data model may or may not be appropriate. Of course, this is a start. As Deshpande pointed out, users can always step in to refine their graph data model using TigerGraph’s visual IDE.
Over time, Deshpande said, the ability to control the process will be added. For now, however, users should be aware of this and be ready to step in when needed. But that’s not all they can want to use TigerGraph’s visual for. IDE for. Overall, visual environments are a tremendous asset for developer accessibility and productivity, and graphics database vendors have added them to their arsenals as well.
TigerGraph 3.0, however, goes one step further. To our knowledge, an industry first, TigerGraph 3.0 introduces visual query capabilities for its IDE. In other words: users can now explore their charts, formulate and execute queries against the database, without actually learning TigerGraph’s query language or writing code.
This patent pending capability will likely attract attention and help alleviate one of the problems with graph databases. While efforts to produce a universally standardized graphical query language are underway, no code query is an attractive capability in and of itself.
Leveraging Connections in the Era of COVID-19
TigerGraph 3.0 introduces more enhancements, namely support for distributed environments in its cloud and user-defined indexing. The former means that graph deployments around the world can now scale more efficiently, while the latter means that users can speed up database performance for specific queries.
Last but not least, however, is an initiative that comes at a time when chart analysis could really help society as a whole. As the spread of thehas reached pandemic status, according to the WHO, one of the key aspects of the fight against the virus is to identify the contacts for each individual who has tested positive.
It basically comes down to leveraging connections, as the name of the game is to identify people with whom positive COVID-19 cases have come in contact. The idea is to identify potential upstream sources from which the virus may have been acquired while keeping an eye out for potential downstream contacts to try and contain new contamination.
This is exactly the type of analysis where the chart shines. Mastercard, the Bill & Melinda Gates Foundation and Wellcome have launched an initiative to accelerate the development and access to therapies for COVID-19. TigerGraph has taken note of this and would like to lend a hand to this and all other initiatives aimed at stopping the spread and improving treatment of the coronavirus around the world.
For this reason, TigerGraph offers free use of Cloud and Enterprise Edition for applications requiring big data or high computational needs. Local, state, and federal agencies, businesses, and nonprofits can immediately use the free tier on TigerGraph Cloud to upload data and perform advanced analytics.
Graph algorithms can be useful here. For example, Community Detection can identify clusters of viral infections, PageRank can identify super-spread events, and Shortest Path can help understand the origin and impact of the spread in a particular area or community.
TigerGraph’s own founding team has roots in China, and some of its executives have almost escaped blockage in Europe due to the recently imposed travel ban. That may have served as motivation for TigerGraph, but anyway, in times like these, everyone should participate as much as they can.