ArangoDB Hot Backup – Creating consistent cluster-wide snapshots

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Introduction

“Better to have, and not need, than to need, and not have.”
Franz Kafka

Franz Kafka’s talents wouldn’t have been wasted as DBA. Well, reasonable people might disagree.

With this article, we are shouting out a new enterprise feature for ArangoDB: consistent online single server or cluster-wide “hot backups.”

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ArangoML Pipeline – A Common Metadata Layer for Machine Learning Pipelines

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Over the past two years, many of our customers have productionized their machine learning pipelines. Most pipeline components create some kind of metadata which is important to learn from.

This metadata is often unstructured (e.g. Tensorflow’s training metadata is different from PyTorch), which fits nicely into the flexibility of JSON, but what creates the highest value for DataOps & Data Scientists is when connections between this metadata is brought into context using graph technology…. so, we had this idea… and made the result open-source.

We are excited to share ArangoML Pipeline with everybody today – A common and extensible metadata layer for ML pipelines which allows Data Scientists and DataOps to manage all information related to their ML pipelines in one place.

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libgcc: When exceptions collide

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This is a story of an excursion to the bottom of a deep rabbit hole, where I discovered a foot gun in gcc‘s libgcc. The investigation has cost me several days and I hope that by writing this up I can entertain others and save them the journey.

TL;DR

If a C++ application is compiled with GCC on Linux and statically linked against a non-GLibC C-library (like libmusl), then there is a danger of a data race which leads to a busy loop happening after main() and all static destructors have finished. The race happens, if the application does not use pthread_cancel explicitly and if the very first exception which is thrown in the processes’ life is thrown in two different threads at the same time.
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Multi-Model Database ArangoDB 3.5 released – Distributed Joins, Streaming Transactions, extended GraphDB & Search Capabilities

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With this new release we didn’t wait until Christmas again 🙂

No seriously, 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.

Need to know more about multi-model?

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Maybe good to know: Our Managed Service offering, ArangoDB Oasis, will run the full Enterprise Edition of ArangoDB 3.5 including all security as well as special features. You can find more about ArangoDB Oasis and join the Early Bird list on our Managed Service page.

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

Welcome Matt Ekstrom, CRO, and Jörg Schad, Head of Engineering & Machine Learning!

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We are super excited to share the great news of two highly-experienced minds joining team ArangoDB to shape and grow the multi-model vision with us.

Matt Ekstrom is an accomplished enterprise sales leader and joins ArangoDB as Chief Revenue Officer. He brings over 20 years of sales and leadership experience with him and will lead our global sales efforts from San Francisco.

Our new Head of Engineering & Machine Learning is Jörg Schad who brings nearly a decade of experience of researching, designing and developing distributed systems and machine learning pipelines to our team. Read more

RC7 of ArangoDB 3.5: Streaming Transactions API

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We are closing in on the general availability of ArangoDB 3.5. With this (hopefully) last release candidate for the new version, we want to highlight a pretty neat new feature, which many of you requested – a much simpler way to use ACID transactions without the need to write any Javascript code.

Get the latest Releaseof ArangoDB 3.5: Community and Enterprise.

Before we dive in, we want to send another big THANK YOU to the many Avocaderas and Avocaderos who took the release candidates for a spin and shared their findings with us. Immensely helpful for the whole team to learn where we were wrong and right. Thanks, everyone! Read more

RC4 of ArangoDB 3.5: Configurable Analyzers & other ArangoSearch Upgrades

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Step-by-step we are getting closer and closer to the official release of ArangoDB 3.5. First of all, we want to send a biiiiig “Thank You!” to all the testers so far and all your feedback! Super helpful for us!

This Release Candidate post is dedicated to the four new features of ArangoSearch which extend the capabilities and provide pretty huge performance improvements, especially for queries including search & sorting. Read more