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The world is a graph: How Fix reimagines cloud security using a graph in ArangoDB

Estimated reading time: 5 minutes

‘Guest Blog’

Estimated reading time: 5 minutes

In 2015, John Lambers, a Corporate Vice President and Security Fellow at Microsoft wrote “Defenders think in lists. Attackers think in graphs. As long as this is true, attackers win.ˮ

The original problem in cloud security is visibility into my assets. If security engineers donʼt know what cloud services are running, they canʼt protect an environment. Unfortunately, first generation cloud security products were built with a list mindset, i.e. “rows and columnsˮ. They generate a list of assets and their configurations – but show no context of..

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Three Ways to Scale your Graph

Estimated reading time: 10 minutes

Estimated reading time: 10 minutes

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Why Should You Care About SOC 2?

Estimated reading time: 4 minutes

And by the way, ArangoDB is SOC 2 compliant!

Estimated reading time: 3 minutes

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ArangoDB 3.7 – A Big Step Forward for Multi-Model

Estimated reading time: 9 minutes

Estimated reading time: 7 minutes

When our founders realized that data models can be features, we at ArangoDB set ourselves the big goal of developing the most flexible database. With today’s GA release of ArangoDB 3.7, the project reached an important milestone on this journey.

Watch the the ArangoDB 3.7 Release Webinar.

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On building AQL Query Strings

Estimated reading time: 2 minutes

I recently wrote two recipes about generating AQL query strings. They are contained in the ArangoDB cookbook by now:

After that, Github user tracker1 suggested in Github issue 1457 to take the ES6 template string variant even further, using a generator function for string building, and also using promises and ES7 async/await.

We can’t use ES7 async/await in ArangoDB at the moment due to lacking support in V8, but the suggested template string generator function seemed to be an obvious improvement that deserved inclusion in..

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Lockfree protection of data structures that are frequently read

Estimated reading time: 11 minutes

Motivation

In multi-threaded applications running on multi-core systems, it occurs often that there are certain data structures, which are frequently read but relatively seldom changed. An example of this would be a database server that has a list of databases that changes rarely, but needs to be consulted for every single query hitting the database. In such situations one needs to guarantee fast read access as well as protection against inconsistencies, use after free and memory leaks.

Therefore we seek a lock-free protection mechanism that scales to lots of threads on modern machines and..

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Securing your Foxx with API Keys

Estimated reading time: 2 minutes

ArangoDB’s Foxx allows you to easily build an API to access your data sources. But now this API is either public or restricted to users having an account, but those still get unlimited access.

In many use cases you do not want to expose your data in this fashion, but you want to expose it with a more controllable access pattern and want to restrict the requests one user could issue in a certain time period. Popular examples for these API restrictions are Twitter or Facebook. This allows you to offer all of your data but only in limited chunks, and then possibly charge your customers to..

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