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The Year of the Graph

What is a graph database? Do you really need one, and if yes, how do you choose?

The Year of the Graph 2018

Do you really know the answers to those questions? Are you in the 51% of organizations using graph databases? Either way, you are at the right place to get answers.

 

Graph databases have been around for more than 15 years, but it was AWS and Microsoft getting in the domain that attracted widespread interest. If they are into this, there must be a reason.

 

Everyone wants to know more, few can really keep up and provide answers. And as this hitherto niche domain is in the mainstream now, the dynamics are changing dramatically. Besides new entries, existing players keep evolving. I’ve done the hard work, so you don’t have to.

 

This is why this is the best place to find out which is the right solution for you:

I’ve been working with graph databases since 2005, when i implemented my first graph database prototype. This includes award-winning R&D, startups, enterprise deployments, and consulting the (then) top Graph Database vendor on distributed queries in 2008.


I’ve been active as an analyst, consultant and entrepreneur since 2012. Some highlights –defining and analyzing Agile Business Intelligence long before the Gartners of the world, and working with the likes of Hortonworks, SAP, and more.


I’ve been monitoring graph databases for ever, publishing the Year of the Graph newsletter since 2018.

The Year of the Graph Report

Sure, this is not the only available research on graph databases. If you are looking for primers, last year’s overpriced business briefs, or yesteryear’s fragmented analysis, you can check those out.

If you are looking for

  • Up to date, comprehensive, unbiased research by an analyst with hands-ón expertise
  • A unique methodology, combining data & metrics on business and technical aspects

Then the Year of the Graph Report is what you need. Many levels up, at a fraction of the price.


 

Impressive work. Well done. I’m not aware of another source that is as comprehensive as this one. Thank you for that as it’s providing me value from a graph market research perspective.

Jonathan Lacefield, Senior Director of Product Management, DataStax Enterprise Server


Kudos to you for your relentless work on informing the community about their options in the graph sphere. Think the report will be highly appreciated – it’s on a whole different level!

Jan Stücke, Head of Communications, ArangoDB


Anadiotis may understand MarkLogic better than we do ourselves.

Rob Lawrence, former Director or Strategic Programs, MarkLogic

What you get

What you get when you buy the Year if the Graph Report is a bundle that includes:

  • The report. 40 pages of research, with key point summaries and images
  • Access to updates. The report will be updated regularly. Buying once gives you lifetime access to future releases, free or at reduced pricing.

 

Some key points:

It is important to define what a graph database is and what it is not.
A number of solutions offer graph-related features or analytic capabilities.
We define graph databases as the ones having the ability to fully support operational applications utilizing a graph data model and API.
The major choice when it comes to graph databases is the one regarding graph data models.
LPG (Labeled Property Graph) and RDF (Resource Description Framework) are the two options.
Databases utilizing each tend to have specific characteristics, making them more suitable for specific use cases.
Not being based exclusively on a graph data model does not necessarily mean being ruled out.
Multi-model graph databases support LPG or RDF, plus models such as key-value and document.
This makes for a more diverse platform, albeit possibly at the expense of optimizing for graph.
Cloud-only solutions from AWS and Microsoft are different from the rest and from each other.
Their features in terms of scalability and availability appear similar.
Their technical features are different, and they are at different maturity points.

The Year of the Graph Newsletter

If you knew and loved the newsletter, worry not. It’s not going away, and it’s always free.

 

Every month i will publish and comment on the 10 top Graph database related news items.

 

Why me? Ever since i implemented my first graph database prototype in 2005, i have worked on award-winning research, consulted the (then) leading vendor on distributed query implementation, and lead teams of all sizes and shapes working with graph databases.

 

I have also published a number of reports and articles with analysis on big data, distributed systems and analytics with Gigaom and ZDNet. Perhaps more importantly though:

 

I work for nobody else but me, and by extension, you. No fluff, just stuff. No automatically harvested or sponsored posts. No vendor affiliations or hidden agendas. Just hand picked, curated content, and objective, concise analysis.

 

Would you like to receive the latest Year of the Graph Newsletter in your inbox? Easy – just signup below. Have some news you think should be featured in an upcoming newsletter? Easy too – drop me a line here.

EditionMonthSummary
3June 20181. AWS Neptune goes GA 2. Azure CosmosDB new features 3. GQL - a proposal for property graph query language 4. TigerGraph launches free developer edition 5. Practical Gremlin guide new edition 6. Type-safe Gramlin graph queries 7. Data science and graph databases 8. Enterprise knowledge graphs in the real world 9. Repaying the GDPR Data Governance Debt with Metadata and Semantics 10. Why JSON-LD is a good idea
2May 20181. DataStax Enterprise Graph 6.0: what’s new, and what’s coming? 2. What's New in Neo4j 3.4 3. Ontotext’s New GraphDB 8.5 4. What Are Graph Queries, Graph Algorithms And Graph Analytics? 5. How to explain index-free adjacency to your manager 6. MDM and Graph 7. Looking under the hood at Amazon Neptune 8. WebVOWL - Web-based Visualization of Ontologies 9. Transforming JSON output of SPARQL queries 10. Review prediction with Neo4j and TensorFlow
1April 20181. Why the year of the graph 2. Building a model for event data as a graph 3. Fishing for graphs in a Hadoop data lake 4. Graphs as the front end for machine learning 5. Harmonizing big data with an enterprise knowledge graph 6. Making true connections in a complex world 7. Ontology, Meaning and Knowledge Management 8. Neo4j: A Reasonable RDF Graph Database & Reasoning Engine 9. Ted Wilmes on the state of JanusGraph 2018 10. Back to the future: Does graph database success hang on query language?
4July 20181. The Year of the Graph report 2. Graph DBs (CAGR) of 24.0%, market size of USD 2,409.1 million by 2023 3. A practical guide to graph databases 4. Graph tips and tricks 5. Tips for using the Gremlin API 6. Time traveling with graph databases 7. Distributed Graphs Processing With Spark GraphX 8. Selecting a Graph Query Language 9. Symbolic Methods Coming Back 10. CLEVR, a dataset for graph based reasoning 11. AI tool "DIG" exposes sex rings
5September 20181. Knowledge Graphs - Connecting the Dots in an Increasingly Complex World 2. The biggest knowledge graph ever 3. How Do You Know If a Graph Database Solves the Problem? 4. Building Semantic Data Catalogs 5. Hubs & Authorities in Ethereum 6. Similarity search with Machine Learning in Stardog 7. Graphs and ML: Multiple Linear Regression 8. Neo4j Graph View Editor 9. Apache Tinkerpop IDE 10. Spring Data Gremlin for Azure Cosmos DB Graph API 11. SPARQL to Gremlin query bridge 12. Subgraphs in R using Gremlin 13. Ubiquity of Large Graphs and Surprising Challenges of Graph Processing 14. AWS Neptune vs TigerGraph benchmark
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