Little do we know how popular cloud services such as Google, Yahoo, Bing, Twitter, Facebook, Pinterest, LinkedIn, Google+ and Web-based email have not only improved the way people interconnect, socialize and do business, they also help improve our search for information on the Web.
But they have, and significantly so. Because computers and networks remember everything we do when we punch a keyboard, click on a Website or touch a virtual keyboard, those massive logs of data saved by networks are now leading us into a new world of search: graph search.
Graph search, an open-source database project built on all the networking we do online every day, is the most far-reaching search IT to go mainstream since Google started storing up and ranking Websites more than a decade ago. Basically, a graph search database anonymously uses all the contacts in all the networks in which you work to help you find information. Anything you touch, any service you use and anything people in your networks touch eventually can help speed information back to you. It avoids anything non-relevant that would slow down the search.
How It Stands Apart From Standard Databases
Here’s a typical use case: You might be looking for a particular type of restaurant in New York City–say Vietnamese. Using a graph search engine–let’s deploy the one now powering Facebook’s internal search–you enter a query (i.e., “Vietnamese restaurant in midtown Manhattan”); the graph search database then connects all the dots in your friends’ accounts and identifies whether they’ve talked about, photographed or reviewed Vietnamese restaurants in midtown Manhattan. It looks at previous queries about Vietnamese restaurants you have made yourself in the past, it looks at the local geographic area where you currently are, and then it delivers those search results to you in microseconds.
The result is that you get a much more relevant type of search via people with whom you are connected–not a list of Web pages based on keywords that may or may not satisfy your query.
Rapidly Gaining Market Share
Graph databases are rapidly growing in usage, although most people are not aware of them. From Websites adding social-network features to telecoms providing personalized customer services to bioinformatics research, organizations are adopting graph databases as an efficient way to model and query already-connected data. Most of the growth of the genre thus far has been the result of word-of-mouth among database admins and CTOs.
Facebook put graph search on the mainstream IT map last January when Mark Zuckerberg announced it was going into early adopters’ accounts. In July it went into general availability on the site. Other companies are now coming out with their own versions of the database based on the open-source model.
The world’s largest social network also revealed on Oct. 15 that it is planning to roll out Graph Search for its iOS application and for its Messenger app. That is expected to happen sometime in November.
Interestingly, although Facebook has made graph search widely known and freely available within its own environment, the social network did not invent the technology; it started as an open-source project in the late 1990s.
Pioneer of Graph Search Database: Neo Technology
Neo Technology researchers in Sweden have pioneered graph databases–they’ve been working on them since 2000–and have been instrumental in bringing them to a growing number of enterprises worldwide. Among those are Global 2000 companies such as Cisco Systems, Accenture, Deutsche Telekom and Telenor.
Neo Technology recently conducted its second annual GraphConnect conference in San Francisco (Oct. 3 and 4) to gather some of its developer community and customers and talk about continuing development of the platform.
Why Graph Search Is Moving Databases to a New Level
After a full decade in production, Neo4j is now the world’s most widely used graph database with the largest ecosystem of partners, 100-plus paying customers and tens of thousands of successful deployments, Neo Technology founder, chief engineer and CEO Emil Eifrem told eWEEK.
Neo4j is a highly scalable open-source graph database that supports the ACID properties of transactions (atomicity, consistency, isolation and durability), has high-availability clustering for enterprise deployments, and comes with a Web-based administration tool that includes full transaction support and visual node-link graph explorer. Neo4j is accessible from most programming languages using its built-in REST web API interface.
Most of the Tier 1 all-purpose IT companies–such as IBM, EMC, Google, Oracle, Microsoft, and Cisco Systems–either have a graph search database already in use or are close to making their own version available soon. Microsoft’s Horton, VelocityGraph, VertexDB, Sqrrl Enterprise, Oracle Spatial and Graph, OpenLink Virtuoso are among the other graph databases.
Freemium Business Model
Because Neo4j has a freemium business model, it’s nearly impossible to determine how many deployments of the database are now in use, but Eifrem said the numbers of database developers in the Neo community who identify themselves in email lists, meetups and other group activities has tripled year-to-year. Bottom line: There’s no question that interest in the specialized search database is on a clear upswing.
“There’s a lot of value in figuring out how things are related,” Eifrem said. “How people are related, how companies are related–it even could be between proteins interacting. That’s a graph search. For another example: I was running late coming here [to San Francisco] from San Mateo–that’s also a graph search: San Mateo is one node, there’s San Francisco, and between us there are other cities, and their relationships are roads. How do I get from point A to point B? That’s graph search.”
Thus, graph search is widely applicable for a great many use cases. “The key distinction, however, is that very few people have the resources of Mark Zuckerberg and can hire the smartest guys from Google and dedicate hundreds of people to building this out,” Eifrem said.
Neo Technology offers this capability off the shelf, Eifrem said.
Use Case: Onefinestay.com
Neo Technology customer Onefinestay.com is a cloud service for travelers to cities such as London, Paris and New York that enables users to “live like a local.” The business model offers a customer the opportunity to live in a distinctive home while the owner is out of town. Homes on Onefinestay are equivalent to (or exceed, in most cases) a 5-star hotel and include extras such as an iPhone loaded with the contacts for the homeowner’s favorite restaurants and a list of places to explore around town.
With Onefinestay’s growing menu of services and ever-expanding property listings, the company needed a better way to provide insights to its guests and operations team, Eifrem said.
Onefinestay began experiencing more and more database query and standardizations issues, and for this reason, it started looking into other database options, including graph databases.
“We considered a number of NoSQL options, including Mongo, DynamoDB and other graph solutions, Neo4j provided the required balance of features and support we needed to unlock the power of data captured on our residential properties,” said Jackson Hull, CTO of Onefinestay. “Neo4j gives us peace of mind; it’s a solid tool with wide-ranging application, offers a stable partner to grow with, and allows us to be a part of a great user community.”
Works Across Verticals
The Neo4j Graph Database can fit into just about every industry, Eifrem said.
“From telcos to financial services to hospitality to online dating and health care, it is becoming clear that it’s not just about data anymore, but about knowing the relationships between data,” Eifrem said. “Augmenting business decisions with knowledge of how things are connected is becoming a major differentiator for businesses.”
Neo Technology is privately held and funded by Fidelity Growth Partners Europe, Sunstone Capital and Conor Venture Partners, and is headquartered in San Mateo, Calif., with offices in Sweden, the UK, Germany and Malaysia. For more information, go here.