ArangoML Series: Multi-Model Collaboration

Estimated reading time: 8 minutes

Multi-Model Machine Learning

This article looks at how a team collaborating on a real-world machine learning project benefits from using a multi-model database for capturing ML meta-data.

The specific points discussed in this article are how:

  • The graph data model is superior to relational for ML meta-data storage.
  • Storing ML experiment objects is natural with multi-model.
  • ArangoML promotes collaboration due to the flexibility of multi-model.
  • ArangoML provides ops logging and performance analysis.
ArangoML Pipeline Complete pipeline - ArangoDB Machine Learning
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ArangoML Series: Intro to NetworkX Adapter

Estimated reading time: 3 minutes

This post is the fifth in a series of posts introducing the ArangoML features and tools. This post introduces the NetworkX adapter, which makes it easy to analyze your graphs stored in ArangoDB with NetworkX.

In this post we:

  • Briefly introduce NetworkX
  • Explore the IMDB user rating dataset
  • Showcase the ArangoDB integration of NetworkX
  • Explore the centrality measures of the data using NetworkX
  • Store the experiment with arangopipe

This notebook is just a slice of the full-sized notebook available in the ArangoDB NetworkX adapter repository. It is summarized here to better fit the blog post format and provide a quick introduction to using the NetworkX adapter. 

ArangoML Pipeline Cloud graphic showing an example machine learning pipeline
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Neo4j Fabric: Scaling out is not only distributing data

Estimated reading time: 3 minutes

Neo4j, Inc. is the well-known vendor of the Neo4j Graph Database, which solely supports the property graph model with graphs of previously limited size (single server, replicated).

In early 2020, Neo4j finally released its 4.0 version which promises “unlimited scalability” by the new feature Neo4j Fabric. While the marketing claim of “scalability” is true seen from a very simplistic perspective, developers and their teams should keep a few things in mind – most importantly: True horizontal scalability with graph data is not achieved by just allowing distributing data to different machines. Read more

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ArangoDB 3.5 Released: Distributed Joins & Transactions

We are super excited to share the latest upgrades to ArangoDB which are now available with ArangoDB 3.5. With the fast-growing team, we could build many new and long-awaited features in the open-source edition and Enterprise Edition. Get ArangoDB 3.5 on our download page and see all changes in the Changelog.

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Maybe good to know: Our Cloud Service offering, ArangoDB ArangoGraph, will run the full Enterprise Edition of ArangoDB 3.5 including all security as well as special features. You can find more about ArangoDB ArangoGraph and play around for 14-days free in the cloud.

Join the upcoming ArangoDB 3.5 Feature Overview Webinar to have a detailed walkthrough on the release with our Head of Engineering and Machine Learning, Jörg Schad. Read more

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ArangoDB 3.5 RC1: Graph Database Improvements

After a lot of planning, coding and testing we can finally share the first Release Candidate of ArangoDB 3.5 with you today. You can get it on our Technical Preview Download page: Community & Enterprise.

With this RC, we want to highlight two new features for all graph database enthusiasts: the new PRUNE Keyword & k Shortest Path Feature. As always, please note Release Candidates are for testing purposes only and should not be used in production. Please see limitations of RC1 at the bottom of the page! Read more

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What Makes ArangoDB a Graph Database?

When looking for a solution for your project, it is important to understand what makes each technology unique, what sets it apart. With ArangoDB that is its native multi-model approach including full graph database capabilities and I am going to explain the fundamental pieces of what that means. Read more

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Time traveling with graph databases

Graph databases are often used to analyze relations within highly interconnected datasets. Social networks, recommendation engines, corporate hierarchies, fraud detection or querying a bill of materials are common use cases. But these datasets change over time and you as a developer or data scientist may want to time travel and analyze these changes.

While ArangoDB may not come with built-in support for managing the revision history of graph data, we’ll show in this article how to manage it in a performant manner for some general classes of graphs. Best of all, this won’t require any groundbreaking new ideas. We’ll simply borrow a few tools and tricks from the persistent data structure literature and adapt them for good performance within ArangoDB. We hope that this will help enable new ways to use everyone’s favorite avocado-fueled datastore, and power some useful applications. Read more

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ArangoDB Named Best Free Graph Database by G2 Crowd Users

ArangoDB named by G2 Crowd users as the most popular graph database used today.

ArangoDB has been identified as the highest rated graph database, based on its high levels of customer satisfaction and likeliness to recommend ratings from real G2 Crowd users.

ArangoDB received a near perfect 4.9 out of 5 star average for user satisfaction for its free platform across its 24 user reviews. ArangoDB users point to the database’s query language, availability and storage as the three most liked features of the product. Read more

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ArangoDB | Infocamere Investigation: Graph Databases Case Study

InfoCamere is the IT company of the Italian Chambers of Commerce. By devising and developing up-to-date and innovative IT solutions and services, it connects the Chambers of Commerce and their databases through a network that is also accessible to the public via the Internet. Thanks to InfoCamere, businesses, Public Authorities, trade associations, professional bodies and simple citizens – both in Italy and abroad – can easily access updated and official information and economic data on all businesses registered and operating in Italy.

The Italian Chambers of Commerce are public bodies entrusted to serve and promote Italian businesses through over 300 branch offices located throughout the country. InfoCamere helps them in pursuing their goals in the interest of the business community. On behalf of the Chambers’ System, InfoCamere plays a key-role in implementing the Italian Digital Agenda with respect to the digital transformation process of the national productive system, especially focusing on supporting the digitalization of SMEs.

Guest post by Luca Sinico (Software Developer, InfoCamere)

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ArangoDB Webinar: Apps with ArangoDB & KeyLines

Wednesday, September 6th (5PM CEST/11AM ET/8AM PT) – Join the webinar here

Cambridge Intelligence KeyLines and ArangoDBAs data gets bigger, faster and more complex, you need to arm yourself with the best tools. In this webinar we’ll see how KeyLines and ArangoDB combine to create powerful and intuitive data analysis platforms. Read more

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