The ArangoDB Platform

The ArangoDB Platform brings everything ArangoDB offers together to a single solution that you can deploy on-prem or use as a managed service

The ArangoDB Platform & GenAI Suite is available as a pre-release. To get exclusive early access, get in touch with the ArangoDB team.

The ArangoDB Platform is a technical infrastructure that acts as the umbrella for hosting the entire ArangoDB offering of products. The Platform makes it easy to deploy and operate the core ArangoDB database system along with any additional ArangoDB products for machine learning, data explorations, and more. You can run it on-premises or in the cloud yourself on top of Kubernetes to access all of the platform features.

Features of the ArangoDB Platform

Core database system: The ArangoDB graph database system for storing interconnected data.
Graph Visualizer: A web-based tool for exploring your graph data with an intuitive interface and sophisticated querying capabilities.
Graph Analytics: A suite of graph algorithms including PageRank, community detection, and centrality measures with support for GPU acceleration thanks to Nvidia cuGraph.
GenAI Suite: A set of machine learning services, APIs, and user interfaces that are available as a package as well as individual products.
- GraphML: A turnkey solution for graph machine learning for prediction use cases such as fraud detection, supply chain, healthcare, retail, and cyber security.
- GraphRAG: Leverage ArangoDB’s graph, document, key-value, full-text search, and vector search features to streamline knowledge extraction and retrieval.
  - GraphRAG Importer: Extract entities and relationships from large text-based files, converting unstructured data into a knowledge graph stored in ArangoDB.
  - GraphRAG Retriever: Perform semantic similarity searches or aggregate insights from graph communities with global and local queries.
  - Public and private LLM support: Use public LLMs such as OpenAI or private LLMs with Triton Inference Server.
  - MLflow integration: Use the popular MLflow as a model registry for private LLMs or to run machine learning experiments as part of the ArangoDB Platform.
Jupyter notebooks: Run a Jupyter kernel in the platform for hosting interactive notebooks for experimentation and development of applications that use ArangoDB as their backend.

Get started with the ArangoDB Platform

Use the ArangoDB Platform as a managed service

The ArangoDB Platform is not available as a managed service yet, but it will become available for the ArangoGraph Insights Platform in the future. Until then, you can request early access to the self-hosted ArangoDB Platform for testing.

Self-host the ArangoDB Platform

You can set up and run the ArangoDB Platform on-premises or in the cloud and manage this deployment yourself.

Requirements for self-hosting

Early access to the ArangoDB Platform: Get in touch with the ArangoDB team to get exclusive early access to the pre-release of the ArangoDB Platform & GenAI Suite.
Kubernetes: Orchestrates the selected services that comprise the ArangoDB Platform, running them in containers for safety and scalability.
Set up a Kubernetes cluster if you don’t have one available yet.
kubectl: A command line tool for communicating with a Kubernetes cluster’s control plane.
Install kubectl for applying specifications such as for creating the ArangoDB Core deployment, as well as for checking pods, logs, etc.
Helm: A package manager for Kubernetes.
You need to have helm installed in order to install the required certificate manager and the ArangoDB Kubernetes Operator as part of the Platform setup.
Container registry: A repository for storing and accessing container images.
You need to have a container registry for installing the images of the Platform services. It can be a local registry.

Setup

Obtain a zip package of the ArangoDB Platform for the offline installation. It includes helm charts, manifests, and blobs of the container image layers. You also receive a package configuration file from the ArangoDB team.

Create a Kubernetes namespace for ArangoDB and a secret with your Enterprise Edition license key. Substitute <license-string> with the actual license string:

kubectl create namespace arangodb

kubectl create secret generic arango-license-key \
  --namespace arangodb \
  --from-literal=token-v2="<license-string>"

Install the certificate manager. You can check https://github.com/cert-manager/cert-manager for the available releases.

VERSION_CERT='1.18.2' # Use a newer version if available
helm repo add jetstack https://charts.jetstack.io
helm repo update

helm upgrade --install cert-manager \
  --namespace cert-manager --create-namespace \
  --version "v${VERSION_CERT}" \
  jetstack/cert-manager \
  --set crds.enabled=true

Install the ArangoDB operator for Kubernetes kube-arangodb with helm, with options to enable webhooks, certificates, and the gateway feature.

VERSION_OPERATOR='1.3.0' # Use a newer version if available

helm upgrade --install operator \
  --namespace arangodb \
  "https://github.com/arangodb/kube-arangodb/releases/download/${VERSION_OPERATOR}/kube-arangodb-enterprise-${VERSION_OPERATOR}.tgz" \
  --set "webhooks.enabled=true" \
  --set "certificate.enabled=true" \
  --set "operator.args[0]=--deployment.feature.gateway=true" \
  --set "operator.features.platform=true" \
  --set "operator.features.ml=true" \
  --set "operator.architectures={amd64}" # or {arm64} for ARM-based CPUs

Create an ArangoDeployment specification for the ArangoDB Core. See the ArangoDeployment Custom Resource Overview and the linked reference.
You need to enable the gateway feature by setting spec.gateway.enabled and spec.gateway.dynamic to true in the specification. You also need to set spec.license to the secret created earlier. Example for an ArangoDB cluster deployment using version 3.12.5 with three DB-Servers and two Coordinators:
```
apiVersion: "database.arangodb.com/v1"
kind: "ArangoDeployment"
metadata:
  name: "platform-example"
spec:
  mode: Cluster
  image: "arangodb/enterprise:3.12.5"
  gateway:
    enabled: true
    dynamic: true
  gateways:
    count: 1
  dbservers:
    count: 3
  coordinators:
    count: 2
  license:
    secretName: arango-license-key
  # ...
```
Download the ArangoDB Platform CLI tool arangodb_operator_platform from https://github.com/arangodb/kube-arangodb/releases . It is available for Linux and macOS, for the x86-64 as well as 64-bit ARM architecture (e.g. arangodb_operator_platform_linux_amd64).
It is recommended to rename the downloaded executable to arangodb_operator_platform and add it to the PATH environment variable to make it available as a command in the system.
The Platform CLI tool simplifies the further setup and later management of the Platform’s Kubernetes services.
Import the zip package of the ArangoDB Platform into the container registry. Replace platform.zip with the file path of the offline installation package. Replace gcr.io/my-reg with the address of your registry.
```
arangodb_operator_platform package import \
  --registry-docker-credentials \
  gcr.io/my-reg \
  ./platform.zip \
  platform.imported.yaml
```
Install the package using the package configuration you received from the ArangoDB team (platform.yaml) and the configuration generated by the previous command (platform.imported.yaml). These configurations are merged, allowing for targeted upgrades and user-defined overrides.
The package installation creates and enables various services, including the unified web interface of the Platform.
```
arangodb_operator_platform --context arangodb package install \
  --platform.name platform-example \
  ./platform.yaml \
  ./platform.imported.yaml
```

Interfaces

The ArangoDB Platform uses a gateway to make all its services available via a single port at the external address of the deployment. For a local deployment, the base URL is https://127.0.0.1:8529.

Unified web interface

You can access the ArangoDB Platform web interface with a browser by appending /ui/ to the base URL, e.g. https://127.0.0.1:8529/ui/.

ArangoDB Core

The HTTP API of the ArangoDB Core database system is available at the base URL. For example, the URL of the Cursor API for submitting AQL queries (against the _system database) is https://127.0.0.1:8529/_db/_system/_api/cursor.