It’s been a year since I published the Graph Technology Landscape 2019 post on GraphAware’s blog. I consider this a success story because it got a lot of attention and publicity. The landscape was mentioned many times at different places; it was used by Emil Eifrem in his GraphTour and GraphConnect opening keynotes, it was displayed in conference halls, and I received many, many useful comments and feedback. I was even invited to Rik van Bruggen Graphistania Podcast to talk about it, and the episode was referred to in the Top 5 Neo4j Podcasts of 2019 blog posts as well.
A lot of things have happened in this field of technology and in my personal life since then. I finished working as a GraphAware consultant in Abu Dhabi, and I moved back to Budapest to look for new adventures in my professional life. I took a short break as sabbatical leave, and I started to work as a freelancer under the flag of my company called GraphCoding. I felt it should be my responsibility to refresh the landscape and publish the year 2020 version as well, so I started to process all the todo items I saved during the year. My Todoist project contained a lot of general items to complete, and there were more than two hundred new candidates to include into the picture. They are not necessarily new players, some of them are included only because this time I had more time to research and now some new categories have been introduced. I restructured the landscape, and tried to collect the developer resources into a category, where software developers can find all the necessary visualisation and analytics libraries needed to implement graph-based applications.
So, here it is, the new landscape, and I have a few thoughts about what happened in the last year, and what changes were introduced into the picture. Enjoy!
To see the landscape at full size, click here. To view a full list of participants in spreadsheet format, click here.
Databases and infrastructure
This is the core category of the landscape, and these databases are the main drivers of this market. I wanted to keep this category fresh, so I decided to remove obsolete products, where nothing happened in the last 2-3 years. If it is an open-source project, then it can be easily verified by checking the commits in the project repository. This is not recent, but Sqrrl was acquired by Amazon in 2018, and the plan was to include it into Amazon Web Service offerings. The company’s website has not been available since last summer, so It was removed from the landscape. Another database infogrid was removed as well, the website became obsolete. Titan also reached the end of its life state a few years ago. These databases were removed from the graph database category of the db-engines site as well. There is a new common approach for databases to provide some kind of graph API to handle connected data. A lot of traditional database products provide a graph API, like MariaDB, MS SQL Server, Oracle, and IBM. This is the reason for including these databases into the multi-model graph databases category. There were interesting acquisitions and investments as well, they indicated some changes in the products category as well. OrientDB was purchased by Callidus in 2017, and Sap acquired CallidusCloud later, so OrientDB ended up at SAP, and we can see some activities here when it will be merged into the product portfolio of SAP, but there is not much news about it. DGraph received its 11.5m USD Series-A investment in 2019 also, so they are forced to grow in the next few years as well. Trovares received its Series-A money as well, so another graph analytics engine with big hopes. A few companies released the new version of their offering. Tibco released version 2.0 of its graph database last year, and Cambridge Semantics also announced AnzoGraph 2.0 a few days ago. Graph databases is a fast growing market, and this ensures that there are new kids on the block, always. It is true for year 2019 and 2020 as well, we have seen numerous new players arriving. Nebula graph and TerminusDB arrived to the public, and somebody (maybe a tennis fan) had a sense of humor when naming their new graph database Steffi. The cloud native fully managed approach is getting stronger for 2020 and top players are competing in this area strongly. Neo4j rolled out its cloud version, Neo4j Aura, finally, and TigerGraph also announced its hosted cloud version, so another aspiring name if you are looking for cloud native graph database.
Rise of the knowledge graphs
Ebay open sourced its own knowledge graph solution Akutan (formerly Beam), so it is a new logo in the picture. StarDog raised 9m USD SeriesB to strengthen its position in the knowledge graph market. The new TerminusDB targets its database for knowledge graph representation as well. Deloitte’s MissionGraph is also about knowledge management. Finally, GraphAware Hume seems to be gaining traction in the enterprise knowledge graph management space and was mentioned in the recent “Predicts 2020: Artificial Intelligence – the Road to Production” report by Gartner together with some other solutions providers.
Applications
This is a technology landscape but it is important to demonstrate the market of the applications which use these technologies. I collected numerous applications where you can see how graphs can help you to get powerful insights from your data. Of course, it is impossible to list all the applications which try to use graph technology, there are 2500+ applications in the Neo4j startup program only, and this is only one segment of this market. So the application section on the landscape is just a snapshot of this area, but feel free to add more Apps in a comment, if you feel that something is missing.
Books
A couple of good books were published last year, I will recommend a few here. The Graph algorithms book by Mark Needham and Amy E. Hodler was on the landscape last year with its early release, but 2019 was the year when the final book went big with ten thousand downloads. There was a French book earlier from Sylvain Roussy, Nicolas Mervaillie, and Nicolas Rouyer about a project story, and now the updated english version of the book was released as well. There is a complete guide about graph databases, which looks like an interesting read as well from Gerardus Blokdyk. I have found three interesting books in progress, they will be worth the attention when they are published, one is about Knowledge Graphs, the other is a practitioner’s guide to graph data, and the third one about Graph-Powered Machine Learning. The last two are already available with the Early Access program.
Conferences
Last but not least the events where you can meet graph fellows around the world. The Graphday and Global Graph Summit joint forces and this is The Global Graph Summit just happened last week in Texas. Neo4j started the NODES online developer conference in 2019, which was a good opportunity to listen to graph experts without leaving your armchair at home. The product and solution-focused Graph tours are also happening continuously by Neo4j, and there is a new Graphorum event if you are around Chicago.
Epilogue
Finally, again, I want to thank all the comments, mentions, presentations, invites, offered help from people, friends, ex-colleagues, it was a huge motivation factor for me to create the 2020 version of this Graph Technology Landscape. What is next for the landscape? I still do not know, but I have already made some predictions in last year’s podcast with Rik. For me, the next step is to print out this picture and hang it on my room’s wall, and I hope I will have some followers to do the same around the world. Thanks!