Graph Database Market Expected to Reach 2,409.1 Million USD by 2023
The graph database market size was valued at USD 700.0 Million in 2017 and is expected to reach USD 2,409.1 Million by 2023, at a Compound Annual Growth Rate (CAGR) of 24.0%.
Ontotext's GraphDB 8.7 Offers Vector-Based Concept Matching and Better Scalability, Performance and Data Governance
Ontotext is releasing GraphDB 8.7 - the latest version of its semantic graph database adding support for concept-matching in knowledge graphs thanks to a new plugin returning similar terms
Multi-Hop Knowledge Graph Reasoning with Reward Shaping
Multi-hop reasoning is an effective approach for query answering (QA) over incomplete knowledge graphs (KGs). The problem can be formulated in a reinforcement learning (RL) setup, where a...
Analyze Amazon Neptune Graphs using Amazon SageMaker Jupyter Notebooks
Whether you’re creating a new graph data model and queries, or exploring an existing graph dataset, it can be useful to have an interactive query environment that allows you to visualize the results. In this blog post we show you how to achieve this by connecting an Amazon SageMaker notebook to an Amazon Neptune database. […]
We’re pleased to announce the start of a multi-part series of posts for Amazon Neptune in which we explore graph application datasets and queries drawn from many different domains and problem spaces. Amazon Neptune is a fast and reliable, fully-managed graph database, optimized for storing and querying highly connected data. It is ideal for online […]
Azure #CosmosDB @ Build 2018: The catalyst for next generation apps
Today at the Microsoft Build Conference 2018 in Seattle, we are excited to announce several new capabilities all of which are intended to enable you to easily build your mission-critical, globally ...
We are pleased to announce that Spring Data Gremlin is now available on Maven Central and source code on GitHub. This project provides Spring Data support for Graph databases that use Gremlin as a ...
The true role graph databases will play in the future of enterprise data management is nuanced. An overview of the Enterprise Data World (EDW) Presentation by CEO Salah Kamel.
I recently posted a few images of a network graph I built with Neo4j depicting the connections between English cases. This article serves as a quick write up on how the graph database and the visualisations where produced.
Transform publicly available BigQuery data and Stackdriver logs into graph databases with Neo4j
Learn how to use Neo4j to integrate a BigQuery public dataset with Stackdriver logs into a graph database, to surface new conclusions from complex data.
Entertainment and lifestyle publisher uses Azure Cosmos DB to power recommendation engine, delight 75 million fans
Acquiring an audience for any website isn’t about hooking readers once. It’s about keeping them coming back. With ambitions to grow, Diply—a leading entertainment and lifestyle publisher based in Canada, with offices in Toronto, London, Ontario, and New York City—turned to Microsoft Azure Cosmos DB to drive personalized article suggestions to entice visitors to read more. Diply found Azure Cosmos DB to be cost-effective, reliable, and scalable. The company plans to use its new extensible infrastructure to further improve results with features such as advanced analytics.