ArangoDB Events
Check out the upcoming ArangoDB Events, including Webinars, Meetups, Conference Talks and more.
Upcoming events
'Graph & Beyond' Lunch Break
#16 – ArangoDB for Beginners
August 11th, 2021 – 12 pm
Join Digital Marketing Manager Laura Cope who will give a basic introduction to ArangoDB and the different services ArangoDB has to offer.
FrOSCon 2021
Chris Woodward “Using GeoJSON Data in a Fullstack Vue Application”
August 21st, 2021 7 AM PDT / 10 AM EDT / 4 PM CEST
This talk will discuss the initial steps in developing a vacation rental application with VueJS, Koa, and ArangoDB. The talk covers what GeoJSON data is, how we used it in our application, and the technologies used for the VueJS frontend. We showcase how to use our built-in full-text search engine ArangoSearch for text information retrieval with the new GeoJSON analyzer.
'Graph & Beyond' Lunch Break
#17 – Introduction to Foxx Microservices
August 25th, 2021 – 12 pm
Sit down with Chris Woodward as he shows you the ingredients that make Foxx work so well and then see how to cook up your first Foxx microservice in this ArangoDB Lunch Session.
Workshop
Graph ML, NVIDIA Triton, and ArangoDB: Thinking Beyond Euclidean Space
September 15, 2021 - 10am PDT/ 1pm EDT/ 7pm CEST
So far we have heard a lot about Convolutional Neural Networks (CNNs) which is a well-known method to handle euclidean data structures (like images, text, speech, and time series). However, in the real world, we are also surrounded by non-euclidean data like graphs, and a machine learning method to handle this type of data is known as the Graph Neural Networks. Therefore, in this workshop, we will deepen our knowledge with the concepts of Graph Neural Networks and compare them with CNNs.
Past events
'Graph & Beyond' Lunch Break
#15 – Entity Resolution
July 28th, 2021 – 12 pm
In this lunch session, we show why a graph database is well-suited for Entity Resolution together with a demo in ArangoDB.
'Graph & Beyond' Lunch Break
#14 – Monitoring ArangoDB
July 14th, 2021 – 12 pm
Calling monitoring services best practice, especially those in production, is surely understated. Not only does one gain insight into resource utilisation and can thus responsibly and optimally adjust the environment for apparent needs, but one is put into the position to understand failures on the application as well as the service side.
ArangoDB exposes tons of metrics counters, values, and histograms. In this lunch session, learn how to set up and read monitoring on ArangoDB instances, and take a walk through of the most significant metrics and discuss alerting based on them.
Workshop
Serving AI Models at Scale with Nvidia Triton
July 08, 2021 - 9am PDT/ 12pm EDT/ 6pm CEST
In this workshop, join Machine Learning Research Engineer Sachin Sharma and learn how to use Nvidia’s Triton Inference server (formerly known as TensorRT Inference Server), which simplifies the deployment of AI models at scale in production. We focus on hosting/deploying multiple trained models (Tensorflow, PyTorch) on the Triton inference server to leverage its full potential for this examination. Once models are deployed, we can make inference requests and can get back the predictions.
Online Meetup
Community Pioneer: “Fast image search using ArangoDB and the Google Vision API”
June 30, 2021 - 11am PDT/ 2pm EDT/ 8pm CEST
Join Chris Woodward and community member Anthony Mahanna in this community pioneer webinar.
Here we discuss how Anthony leveraged ArangoDB’s multi-model capabilities along with the Google Vision API to build Picsum Vision.
'Graph & Beyond' Lunch Break
#13 – Kubernetes Meets Graphs
June 30th, 2021 – 12 pm
Kube-Arango is ArangoDB’s Kubernetes Operator, which by the way also powers ArangoDB’s managed Service Oasis.
We will cover the entire Lifecycle of an ArangoDB Cluster on Kubernetes, starting from deployment, over scaling, to upgrades. Furthermore, we will look into best practices such as Monitoring.
Webinar
ArangoDB 3.8 – Analytics at Scale
June 22, 2021 - 10am PDT/ 1pm EDT/ 7pm CEST
The ArangoDB community and team are proud to release the next version of ArangoDB, an open-source, highly scalable graph database with multi-model capabilities.
With version 3.8, ArangoDB doubles down on its capabilities for Analytics at scale, especially in the area of Graph and ArangoSearch including:
- AQL window operations
- Weighted Graph Traversal
- ArangoSearch Pipeline & AQL Analyzers
- Enhanced Geo support in ArangoSearch
and many more exciting features!
Join our CTO, Jörg Schad, Ph.D. in this webinar to learn more about ArangoDB 3.8 and the roadmap for upcoming releases.
'Graph & Beyond' Lunch Break
#12 – Knowledge Graphs
June 16th, 2021 – 12 pm
This lunch session is an introductory video and focuses on the general concepts of knowledge graphs; the video covers:
- What is a Graph Database?
- What is a Knowledge graph?
- How do you Build a Knowledge Graph?
AI@Enterprise Summit 2021
Jörg Schad “Production-grade ML Pipelines – From Data To Metadata”
June 9th, 2021 – 6:30 – 6:50 PM (CET)
It is well known that data quality and quantity are crucial for building Machine Learning models, especially when dealing with Deep Learning and Neural Networks. But besides the data required to build the model itself, there is another often overlooked type of data required to build a production-grade Machine Learning Platform: Metadata.
Modern Machine Learning platforms contain a number of different components: Distributed Training, Jupyter Notebooks, CI/CD, Hyperparameter Optimization, Feature stores, and many more. Most of these components have associated metadata including versioned datasets, versioned Jupyter Notebooks, training parameters, test/training accuracy of a trained model, versioned features, and statistics from model serving. For the dataops team managing such production platforms, it is critical to have a common view across all this metadata, as we have to ask questions such as: Which Jupyter Notebook has been used to build Model XYZ currently running in production? If there is new data for a given dataset, which models (currently serving in production) have to be updated? In this talk, we look at existing implementations, in particular, MLMD as part of the TensorFlow ecosystem.
'Graph & Beyond' Lunch Break
#11 – Fuzzy Search
June 2nd, 2021 – 12 pm
Fuzzy search is an umbrella term for approximate matching in text retrieval. A common application is to compensate for typos in search phrases. In this Lunch Session, we will take a look at different similarity measures and show how fuzzy search works in ArangoDB.
Data+AI Summit 2021
Jörg Schad “Graph-Powered Machine Learning”
May 26th, 2021 – 12:05 PM (PT)
Many powerful Machine Learning algorithms are based on graphs, e.g., Page Rank (Pregel), Recommendation Engines (collaborative filtering), text summarization, and other NLP tasks. Also, the recent developments with Graph Neural Networks connect the worlds of Graphs and Machine Learning even further.
Considering data pre-processing and feature engineering which are both vital tasks in Machine Learning Pipelines extends this relationship across the entire ecosystem. In this session, we will investigate the entire range of Graphs and Machine Learning with many practical exercises.
'Graph & Beyond' Lunch Break
#10 – Oasisctl: Providing full control of your Oasis Cluster
May 19th, 2021 – 12 pm
In this Lunch Break session, Site Reliability Engineer Marcin Swiderski will give an overview of Oasisctl, a tool created by the ArangoDB Oasis team in order to help automate some common Oasis tasks. You will learn what Oasisctl is, how to use it, and how you can leverage it in your projects. We will cover some common operations that can be automated or included in your CI/CD pipelines.
O'Reilly Live Training
Jörg Schad “Graph Powered Machine Learning First Steps”
Many powerful machine learning algorithms—including PageRank (Pregel), recommendation engines (collaborative filtering), and text summarization and other NLP tasks—are based on graphs. And there are even more applications once you consider data preprocessing and feature engineering, which are both vital tasks in machine learning pipelines.
Join expert Jörg Schad to explore the symbiosis of graphs and machine learning, starting with graph analytics to graph neural networks. You’ll learn why graphs are such a powerful abstraction and discover how to leverage them in your machine learning projects.
'Graph & Beyond' Lunch Break
#9 – ArangoML
May 5th, 2021 – 12pm
In this Graph & Beyond Lunch Session Jörg Schad will give an overview of different parts of the ML pipeline and how ArangoDB fits in. In particular, we will be talking about feature engineering, Graph ML, Embeddings, MLOps, and Metadata.
Spoiler: There will be a number of Jupyter notebooks allowing you to get hands-on experience!
'Graph & Beyond' Lunch Break
#8 – Introduction to ArangoBnB
April 21st, 2021 – 12pm
In this Lunch Break, Developer Relations Engineer Chris Woodward provides a peek at the ArangoBnB project, a Fullstack JavaScript Web App that is being developed to showcase the upcoming ArangoSearch GeoJSON features.
ML Summit 2021
Jörg Schad “Graph Powered Machine Learning”
April 20th, 2021
In this workshop, you will learn about Graph Powered Machine Learning starting with simple graph algorithms, over graph analytics, up to Graph Neural Networks.
In particular, the workshop will cover the following topics:
– Why graphs are such a powerful abstraction
– What use-cases are suitable for Graph-based Machine Learning
– How to leverage knowledge graphs
– The graph ecosystem including its many many powerful open source tools
– How to extract value from graphs using graph analytics and graph algorithms
– How to combine deep learning and graphs
– How we can learn graphs features using graph neural networks
'Graph & Beyond' Lunch Break
#7 – Getting Started with ArangoDB Oasis
April 7th, 2021 – 12pm
Looking to get a glimpse of ArangoDB Oasis, the managed cloud service for ArangoDB?
In this Lunch Break, Senior Software Developer Robert Stam will introduce the Oasis platform.
'Graph & Beyond' Lunch Break
#6 – AQL Query Performance Optimization 101 (Part II)
March 24th, 2021 – 12pm
This is Part 2 of the Lunch Break sessions covering the basics of AQL query performance optimization. This Lunch Break session covers AQL query performance optimizations for cluster setups. It is a follow-up session to the AQL query performance optimization session from 2 weeks earlier.
Codemotion Conference 2021
Jörg Schad “RDF vs. Property Graphs: Friends or Foes?”
When it comes to (knowledge) graphs, the world is divided between RDF and Property Graph. And even in 2021 these camps appear disjoint with some preferring the standardized semantics of RDF while others prefer the ease-of-use and flexibility of property graphs. In this talk we will first discuss the individual strengths and weaknesses of each system and then look at different use-cases (in particular knowledge graphs). Furthermore, we will see that in many cases they are actually best used together, combining their strengths.
O'Reilly Live Training
Jörg Schad “Graph Powered Machine Learning First Steps”
Many powerful machine learning algorithms—including PageRank (Pregel), recommendation engines (collaborative filtering), and text summarization and other NLP tasks—are based on graphs. And there are even more applications once you consider data preprocessing and feature engineering, which are both vital tasks in machine learning pipelines.
Join expert Jörg Schad to explore the symbiosis of graphs and machine learning, starting with graph analytics to graph neural networks. You’ll learn why graphs are such a powerful abstraction and discover how to leverage them in your machine learning projects.
'Graph & Beyond' Lunch Break
#5 – AQL Query Performance Optimization 101 (Part I)
March 10th, 2021 – 12pm
This is Part 1 of 2 Lunch Break sessions covering the basics of AQL query performance optimization. Jan Steemann will check if and how indexes can help AQL query performance, and how to set up the indexes so that they help most.
'Graph & Beyond' Lunch Break
#4 – Graph Analytics with ArangoDB
February 24th, 2021 – 12pm
In this Graph & Beyond Lunch Session you learn about Graph Analytics with ArangoDB. We will take a short look at different graph algorithms such as Community Detection, Centrality Measures, and Recommendation, but also discuss challenges of scaling such analytics to enterprise use cases.
'Graph & Beyond' Lunch Break
#3 – AQL for eCommerce Analytics
February 17th, 2021 – 12pm
During this Lunch Session, Jackson Reimers will showcase various AQL queries to analyze an eCommerce dataset for common questions in retail, such as:
- What products are offered?
- Where are they located in my store?
- Which are the best selling products?
- What can the data tell me about shopper purchasing behaviors?
'Graph & Beyond' Lunch Break
#2 – ArangoSearch – Where Full-Text Search and Graphs Meet
February 10th, 2021 – 12pm
In this Graph and Beyond Lunch session we will cover ArangoSearch, the full-text search engine natively integrated into ArangoDB. Chris Woodward will give an overview of how you can combine a wide range of search queries (e.g., phrase, proximity, or range), ranking (e.g., BM25 or TFIDF algorithms) and ArangoDB’s other data models (e.g., graph or document).
Webinar
Graph Analytics with ArangoDB
February 9, 2021 - 9:30am PT/ 12:30pm ET/ 6:30pm CET
Many powerful Machine Learning algorithms are based on graphs, e.g., Page Rank (Pregel), Recommendation Engines (collaborative filtering), text summarization and other NLP tasks. In this hands-on workshop, we will explore a number of use cases suitable for Graph Analytics — and in particular leverage ArangoDB’s Graph Algorithms Library.
'Graph & Beyond' Lunch Break
#1 – Fraud Detection with ArangoDB
February 3rd, 2021 – 12pm
Learn how to use the multi-model graph capabilities within ArangoDB to identify fraud patterns (as used for money laundering) in financial datasets and catch some bad guys! Jackson Reimers will show various fraud patterns and how to detect them, using the ArangoDB graph visualizer.
Webinar
ArangoDB Webinar: Getting Started with ArangoDB Oasis
January 26, 2021 - 9:30am PT/ 12:30pm ET/ 6:30pm CET
Looking to move to the cloud this year? Curious to get a glimpse of Oasis, the easiest way to run ArangoDB?
Join Ewout Prangsma, ArangoDB Oasis Architect and Team Lead, for a walk-through on how to get started, as well as get the most out of the platform. Topics covered will include:
- Creating your first deployment
- How to choose the right configuration and node size
- Inviting colleagues to join you
- Security best practices
- Introduction to automation with Oasis
- Audience Q&A
O'Reilly Live Training
Jörg Schad “Graph Powered Machine Learning First Steps”
Many powerful machine learning algorithms—including PageRank (Pregel), recommendation engines (collaborative filtering), and text summarization and other NLP tasks—are based on graphs. And there are even more applications once you consider data preprocessing and feature engineering, which are both vital tasks in machine learning pipelines.
Join expert Jörg Schad to explore the symbiosis of graphs and machine learning, starting with graph analytics to graph neural networks. You’ll learn why graphs are such a powerful abstraction and discover how to leverage them in your machine learning projects.
Knowledge Connexions
Jörg Schad “Graph Powered Machine Learning”
Many powerful Machine Learning algorithms are based on graphs, e.g., Page Rank (Pregel), Recommendation Engines (collaborative filtering), text summarization, and other NLP tasks.
There are even more applications once we consider data pre-processing and feature engineering which are both vital tasks in Machine Learning Pipelines.
In this workshop, we will overview the intersection of graphs and Machine Learning from Graph Analytics to Graph Neural Networks.
Join Joerg Schad at 10 AM PT.
Data Science UA Conference
Jörg Schad “Building OpenSource Machine Learning Pipelines”
This workshop gives an overview into building a complete automated deep learning pipeline starting with exploratory analysis, overtraining, model storage, model serving, and monitoring and answer questions such as:
- How can we enable data scientists to exploratively develop models?
- How to automatize distributed Training, Model Optimization, and serving using CI/CD?
- How can we easily deploy these distributed deep learning frameworks on any public or private infrastructure?
- How can we manage multiple different deep learning frameworks on a single cluster, especially considering heterogeneous resources such as GPU?
- How can we store and serve models at scale?
- What Metadata should be stored in a production setup?
- How can we monitor the entire pipeline and track the performance of the deployed models?
The participants will build an end-to-end data analytics pipeline including:
- Pipeline Orchestration with TFX, Kubeflow, and Airflow
- Data preparation
- Jupyter Notebooks
- Distributed training with TensorFlow
- Automation & CI/CD using Jenkins and Argo
- Model and metadata storage
- Model serving and monitoring
Webinar
ArangoDB Feature Preview: Custom Pregel
November 11, 2020 - 10am PT/ 1pm ET/ 7pm CET
Pregel, originally developed by Google, is a framework for iterative, distributed Graph Processing. It has been supported by ArangoDB for almost four years in the form of C++ algorithms. With the upcoming version 3.8 of ArangoDB, we will introduce a more flexible version of Pregel, which will allow users to specify custom Pregel algorithms for a running ArangoDB cluster without having to write C++ code.
In this webinar Heiko Kernbach, software developer at ArangoDB, and Jörg Schad, Head of Engineering, will provide an overview of the new custom Pregel support (which can already be tested using the latest nightly builds). We will have plenty of time at the end for an open discussion about a number of tradeoffs, interface options, and use cases.
All Things Open 2020
Jörg Schad and Chris Woodward: “Challenges in Building Multi-Cloud Provider Platform with Managed Kubernetes”
Building a cloud-agnostic platform used to be a challenging task as one had to deal with a large number of different cloud APIs and service offerings. Today, as most Cloud providers are offering a managed Kubernetes solution (e.g., GKE, AKS, or EKS), it seems like developers could simply build a platform based on Kubernetes and be cloud-agnostic. While this assumption is mostly correct, there are still a number of differences and pitfalls when deploying across those managed Kubernetes solutions.
Chris Woodward: “Hacktoberfest – Intro to Knowledge Graphs”
October 16, 2020 - 10am PDT/ 1pm EDT/ 7pm CEST
Have you ever wondered how Google is able to provide those little information cards when you do a search?
How about how Wikipedia is able to catalog the world’s information and make it useful to humans?
Well, in short, the answer to these questions and many other use cases is that they use Knowledge Graphs.
There are various technologies involved with Knowledge Graphs and getting started with them can seem like a daunting task. However, this meetup is the first in a series that hopes to make Knowledge Graphs more approachable and to show how to utilize them with ArangoDB.
Webinar
Save Time & Do More “Cool Stuff” With Managed Database Service.
October 14, 2020 
Online
If you’re interested in seeing how a managed database can help bring a little Oasis to your life, please join us.
October 14th 2020, 10 AM PDT/ 1 PM EDT/ 7 PM CEST.
DevOpsCon Berlin
Jörg Schad: “Challenges in Building a Multi-Cloud-Provider Platform With Kubernetes”
Building a cloud-agnostic platform used to be a challenging task as one had to deal with a large number of different cloud APIs and service offerings. Today, as most Cloud providers are offering a managed Kubernetes solution (e.g., GKE, AKS, or EKS), it seems like developers could simply build a platform based on Kubernetes and be cloud-agnostic. While this assumption is mostly correct, there are still a number of differences and pitfalls when deploying across those managed Kubernetes solutions.
Developer Week Global: Cloud 2020
Jörg Schad and Chris Woodward: “Challenges in Building Multi-Cloud Provider Platform with Managed Kubernetes “
This talk discusses the experiences made while building the ArangoDB Managed Service offering across and GKE, AKS, or EKS.
Join Joerg and Chris September 29th at 8am PDT.
Webinar
ArangoDB 3.7 – Graph Performance at Scale
September 10, 2020 - 10am PDT/ 1pm EDT/ 7pm CEST
We are excited to share the features and improvements of the latest Arango 3.7 release!
If you want to learn about the latest updates for Graph Performance, Cluster Scalability, Kubernetes Operator improvements, ArangoSearch supporting Fuzzy search, Security, Schema validation, and many more, join Jörg Schad, our Head of Engineering and Machine Learning, in this webinar.
We are looking forward to celebrating the 3.7 release with you and receiving your feedback to make the upcoming releases even better!
Stackconf2020: The Open Source Infrastructure Conference
Jörg Schad: “Challenges in Building a Multi-Cloud-Provider Platform With Kubernetes”
Building a cloud-agnostic platform used to be a challenging task as one had to deal with a large number of different cloud APIs and service offerings. Today, as most Cloud providers are offering a managed Kubernetes solution (e.g., GKE, AKS, or EKS), it seems like developers could simply build a platform based on Kubernetes and be cloud-agnostic. While this assumption is mostly correct, there are still a number of differences and pitfalls when deploying across those managed Kubernetes solutions.
MLOPS: Production and Engineering World 2020
Jörg Schad: “Building an OSS Data Science Pipeline”
Join Joerg Schad for his online workshop “Building an OSS Data Science Pipeline.”
June 16th 2020.
Online Meetup
Community Pioneer: “How and Why I Built my CMS Based on ArangoDB and openresty”
May 20, 2020 Online
Join us and our Community Pioneer, Olivier Bonnaure to learn more about his ArangoDB and openresty project.
May 20th, 2020 – 9AM PST/ 12PM EST/ 6PM CEST
Online Meetup
Community Pioneer: “Monitoring Political and Violent Risks Associated with the COVID-19 Crisis with reKnowledge.”
April 28, 2020 Online
Join us and our Community Pioneer, Julien Grossmann – CEO of reKnowledge, for the next exciting talk on a currently very important topic.
April 28, 2020 – 9AM PST/ 12PM EST/ 6PM CEST
Meetup
JavaScript Armenia Meetup: “Seperate Your Data Access Layer With Typescript Powered Microservices”
April 18, 2020 Armenia
We would like annouce our Community Pioneer Gurgen Hayrapetyan as he explains how he built his own project on ArangoDB.
Saturday, April 18, 2020 from 12:00 PM to 5:00 PM (Armenia Standard Time)
ODSC East 2020
Jörg Schad, Tutorial: “Graph Powered Machine Learning”
Many powerful Machine Learning algorithms are based on graphs, e.g., Page Rank (Pregel), Recommendation Engines (collaborative filtering), text summarization and other NLP tasks. There are even more applications once we consider data pre-processing and feature engineering which are both vital tasks in Machine Learning Pipelines. In this course, we will investigate the intersection of graphs and Machine Learning.
Online Meetup
Community Pioneer: “Machine Learning + Immunology, how ArangoDB Saved My Life”
April 15, 2020 Online Meetup
Join us for the next exciting online talk from our Community Pioneer, Tariq Daouda. During this meetup, Tariq will talk about how he used ArangoDB for managing data set and experiments and for ensuring reproducible results.
April 15, 2020 – 11AM PST/ 2PM EST/ 8PM CEST
Operatorcon
Online Session: “Challenges in Building a Multi-Cloud-Provider Platform With Managed Kubernetes”
April 7, 2020 Online Session
This talk discusses the experiences made while building the ArangoDB Managed Service offering across and GKE, AKS, or EKS. While the (managed) Kubernetes API being a great abstraction from the actual cloud provider, a number of challenges remain including for example networking, autoscaler, cluster provisioning, or node sizing. This talk provides an overview of those challenges and also discuss how they were solved as part the ArangoDB managed Service.
Subscribe to the Webinar and you will receive confirmation per email.
Online Meetup
Community Pioneer: “RecallGraph – A versioning data store for time -variant graphs built on ArangoDB”
March 19, 2020 Online Meetup
We would like welcome you to join a hands-on talk from our Community member – Aditya Mukhopadhyay as he explores RecallGraph – a Foxx Microservice for ArangoDB.
March 19th 2020 – 8:30 AM EDT / 1:30 PM CET / 6 PM IST
Webinar
gVisor, Kata Containers, Firecracker, Docker: Who is Who in the Container Space?
March 11, 2020 - 11am PT/ 1pm ET/ 7pm CET
In this talk, we will provide an overview of the different containerization technologies, discuss their tradeoffs, and provide guidance for different use cases.
* We will define the term container in more detailed during the talk
** and yes we will also cover some of the pre-docker container space!
Join the Head of Engineering and Machine Learning, Jörg Schad in this webinar.
Online Meetup
Community Pioneer Online Meetup: “Separate Your Data Access Layer With TypeScript Powered MicroServices”
March 4, 2020 Online Meetup
We would like to welcome you to the hands-on talk from our Community member – Gurgen Hayrapetyan, who will speak live about his project – ArangoDB Foxx Service Template with TypeScript & Yarn 2.0 Support.
March 4th 2020 – 9AM PT/ 12PM ET/ 6PM CET
Production-grade ML pipelines Meetup
Jörg Schad ” Production-grade ML Pipelines – From Data To Metadata”
February 27, 2020 Zurich, Switzerland
In this talk, we look at existing implementations, in particular, MLMD as part of the TensorFlow ecosystem. Further, we propose the first draft of an (MLMD compatible) universal Metadata API. We demo the first implementation of this API using ArangoDB.
Workshop: Building and Operating an Open Source Data Science Platform
Jörg Schad “Production – grade ML Pipeline”
February 27, 2020 Zurich, Switzerland
This workshop gives an overview into building a complete automated deep learning pipeline starting with exploratory analysis, overtraining, model storage, model serving, and monitoring and answer questions.
Dutch Kubernetes/Cloud-Native Meetup
Jörg Schad & Ewout Prangsma: “Challenges in Building Multi-Cloud-Provider Platform With Managed Kubernetes”
February 19, 2020 Utrecht, Netherlands
This talk discusses the experiences made while building the ArangoDB Managed Service offering across and GKE, AKS, or EKS. While the (managed) Kubernetes API being a great abstraction from the actual cloud provider, a number of challenges remain including for example networking, autoscaler, cluster provisioning, or node sizing. This talk provides an overview of those challenges and also discuss how they were solved as part the ArangoDB managed Service.
Webinar
ArangoML Pipeline Cloud – Manage Machine Learning Metadata
February 13, 2020 - 10am PT/ 1pm ET/ 7pm CET
In this webinar, we will show how to leverage ArangoML Pipeline Cloud with your Machine Learning Pipeline by using an example notebook from the TensorFlow tutorial.
Join our Head of Engineering and Machine Learning, Jörg Schad and our Developer Engineer Chris Woodward, in this release webinar to learn more about the ArangoML Pipeline Cloud and how it can benefit your applications.
Webinar
ArangoDB 3.7 Roadmap: Performance at Scale
February 12, 2020 - 10am PT/ 1pm ET/ 7pm CET
After the release of ArangoDB 3.6 we are starting to work on the next version with even more exciting features. As an open-source project we would love to hear your ideas and discuss the roadmap with our community.
Would you like to learn more about Satellite Graphs, Schema Validation, a number of performance and security improvements?
Than join Jörg Schad, Head of Engineering and Machine Learning at ArangoDB, who will share the latest plans for the upcoming ArangoDB 3.7 release as well as the long term roadmap.
Global Graph Summit/Data Day Texas
ArangoDB @ Global Graph Summit 2020
January 25, 2020 Austin, TX, USA
Look forward to meeting us at the Global Graph Summit 2020 at the ArangoDB booth and more! Details to follow soon.
Webinar
What’s new in ArangoDB 3.6?
January 22, 2020 - 10am PT/ 1pm ET/ 7pm CET
Version 3.6 comes with a new OneShard deployment which is designed for use cases where you don’t need horizontal scalability, but still rely on high availability, fault tolerance and query performance which is similar to a single server. Maybe something for your next Graph use case or multi-tenant application? In this webinar, Ingo Friepoertner, the Product Manager at ArangoDB, will go a into the details on OneShard feature and other several performance improvements introduced with the 3.6 release.
