diff --git a/site/content/data-platform/_index.md b/site/content/data-platform/_index.md index 5b68886243..28547ba9e8 100644 --- a/site/content/data-platform/_index.md +++ b/site/content/data-platform/_index.md @@ -21,6 +21,52 @@ AI solutions for GraphRAG, graph machine learning, data explorations, and more. run it on-premises or in the cloud yourself on top of Kubernetes to access all of the platform features with enterprise-grade automation and reliability. +## What Makes Up the Arango Data Platform + +The Arango Data Platform is built on a layered architecture that combines powerful +components into a unified solution: + +- **ArangoDB Enterprise Edition**: The multi-model database foundation supporting + graphs, documents, key-value, vector search, and full-text search capabilities. + +- **Graph Visualizer**: A sophisticated web-based interface for graph exploration, + smart search, and visual layouts. + +- **Arango Platform Suite**: Enterprise-grade features including high availability + and monitoring, the Graph Analytics Engine, comprehensive APIs and connectors, + and centralized orchestration and resource management. + +All components are orchestrated through Kubernetes, providing automated deployment, +scaling, and management with enterprise-grade reliability. + +For a detailed breakdown of each component, see [Features and Architecture](features/). + +## Extend the Arango Data Platform with AI capabilities + +Extend the Arango Data Platform with the [**AI Suite**](../ai-suite/_index.md) +that offers advanced AI and machine learning capabilities that integrate seamlessly +into the platform's unified web interface. + +What you get with the AI Suite: + +- [GraphRAG](../ai-suite/graphrag/): Generate knowledge graphs from documents and enable + conversational querying of your data. +- [GraphML](../ai-suite/graphml/): Apply machine learning algorithms that leverage graph + structure for better predictions. +- [Graph Analytics](../ai-suite/graph-analytics/): Run advanced algorithms like PageRank + to discover influential nodes and patterns. +- [Jupyter notebooks](../ai-suite/notebook-servers.md): Run Jupyter Notebooks to build and + experiment with graph-powered data, AI, and machine learning workflows directly connected + to ArangoDB databases. +- Public and private LLM support: Use public LLMs such as OpenAI + or private LLMs with [Triton Inference Server](../ai-suite/reference/triton-inference-server.md). +- [MLflow integration](../ai-suite/reference/mlflow.md): Use the popular MLflow as a model registry + for private LLMs or to run machine learning experiments as part of the Arango Data Platform. + +{{< tip >}} +The AI Suite requires a separate license. +{{< /tip >}} + {{< cards >}} {{% card title="Get started with the Arango Data Platform" link="get-started/" %}} @@ -32,8 +78,8 @@ Optionally add AI Suite to turn data into an AI-powered knowledge engine. Explore the Kubernetes-native architecture, unified interface, and enterprise-grade capabilities of the Arango Data Platform. {{% /card %}} -{{% card title="ArangoDB Kubernetes Operator" link="../../arangodb/3.12/deploy/kubernetes/" %}} -Learn about the official ArangoDB Kubernetes Operator that powers the Arango Data Platform. +{{% card title="Kubernetes-Native Architecture" link="kubernetes/" %}} +Learn about the Kubernetes-native foundation that the Arango Data Platform is purpose-built on. {{% /card %}} {{% card title="Graph Visualizer" link="graph-visualizer/" %}} diff --git a/site/content/data-platform/features.md b/site/content/data-platform/features.md index dacda654fa..990e86821f 100644 --- a/site/content/data-platform/features.md +++ b/site/content/data-platform/features.md @@ -1,10 +1,10 @@ --- -title: Feature list of the Arango Data Platform -menuTitle: Features +title: Architecture and Features of the Arango Data Platform +menuTitle: Architecture and Features weight: 5 description: >- - The Arango Data Platform is a scalable Kubernetes-native architecture that gets you all features - of ArangoDB as a single solution with a unified interface + Discover how the Arango Data Platform combines database, visualization, and enterprise + features into a unified, Kubernetes-native architecture --- ## Architecture @@ -18,8 +18,15 @@ scaling, and management. Powered by the official enterprise-grade database management and high availability. {{< /tip >}} -- **Core Database**: The ArangoDB database system forms the solid core - of the Arango Data Platform. +### Kubernetes-Native + +At its core, the Arango Data Platform is purpose-built for Kubernetes environments, leveraging the +[official ArangoDB Kubernetes Operator](https://arangodb.github.io/kube-arangodb/docs/) +(`kube-arangodb`) to deliver enterprise-grade automation, scalability, and operational excellence. + +For detailed information about the Kubernetes foundation, see [Kubernetes Integration](kubernetes/). + +### Technical Infrastructure - **Helm**: A package manager for Kubernetes that enables consistent, repeatable installations and version control. @@ -27,48 +34,60 @@ enterprise-grade database management and high availability. - **Envoy**: A high-performance service proxy that acts as the gateway for the Arango Data Platform for centralizing authentication and routing. -- **Web interface**: The Platform includes a unified, browser-based UI that lets - you access its features in an intuitive way. Optional products like the - AI Suite seamlessly integrate into the UI if installed. +## Platform Components -## Kubernetes Integration +The Arango Data Platform consists of multiple integrated components that work together +to provide a complete, enterprise-ready solution. -At its core, the Arango Data Platform is purpose-built for Kubernetes environments, leveraging the -[official ArangoDB Kubernetes Operator](https://arangodb.github.io/kube-arangodb/docs/) -(`kube-arangodb`) to deliver enterprise-grade automation, scalability, and operational excellence. +### ArangoDB Enterprise Edition -## Features +At the foundation is [**ArangoDB Enterprise Edition**](../../arangodb/3.12/), the +powerful multi-model database that provides: -The Arango Data Platform provides these core capabilities out of the box: +- **Graph**: Native graph database capabilities with efficient traversals and pattern matching +- **Document**: Flexible JSON document storage with schema validation +- **Key-Value**: High-performance key-value operations +- **Vector**: Vector embeddings and similarity search for AI applications +- **Search**: Full-text search and complex query capabilities -- [**ArangoDB Core**](../arangodb/3.12/_index.md): The ArangoDB database system with support for - graphs, documents, key-value, full-text search, and vector search. +### Graph Visualizer -- [**Graph Visualizer**](graph-visualizer.md): - A web-based tool for exploring your graph data with an intuitive interface and - sophisticated querying capabilities. +The [**Graph Visualizer**](graph-visualizer/) provides an intuitive web-based interface +that brings your data to life with: -## Extend the Arango Data Platform with AI capabilities +- **Interactive Graph Exploration**: Visualize named graphs with node expansion, + shortest path discovery, and AQL-powered queries including Canvas Actions that + work with your selection to discover related data + +- **Visual Customization and Layouts**: Customize node colors, icons, and labels + with saveable themes, and apply automatic layout algorithms (force-directed, + hierarchical, circular) with zoom controls and minimap navigation + +- **Direct Graph Editing**: Create, modify, and delete nodes and edges directly + from the canvas with an intuitive properties dialog supporting both form and + JSON editing modes -Take your Arango Data Platform to the next level with the [**AI Suite**](../ai-suite/_index.md) that offers advanced AI and machine learning capabilities that integrate seamlessly into the platform's unified web interface. +The Graph Visualizer seamlessly integrates with the ArangoDB database and provides the +primary interface for data exploration and analysis. -What you get with the AI Suite: +### Arango Platform Suite -- [GraphRAG](../ai-suite/graphrag/): Generate knowledge graphs from documents and enable - conversational querying of your data. -- [GraphML](../ai-suite/graphml/): Apply machine learning algorithms that leverage graph - structure for better predictions. -- [Graph Analytics](../ai-suite/graph-analytics/): Run advanced algorithms like PageRank - to discover influential nodes and patterns. -- [Jupyter notebooks](../ai-suite/notebook-servers.md): Run Jupyter Notebooks to build and - experiment with graph-powered data, AI, and machine learning workflows directly connected - to ArangoDB databases. -- Public and private LLM support: Use public LLMs such as OpenAI - or private LLMs with [Triton Inference Server](../ai-suite/reference/triton-inference-server.md). -- [MLflow integration](../ai-suite/reference/mlflow.md): Use the popular MLflow as a model registry - for private LLMs or to run machine learning experiments as part of the Arango Data Platform. +The **Arango Platform Suite** adds enterprise-grade capabilities such as: -{{< tip >}} -The AI Suite integrate directly into the existing platform interface, no need for -separate systems to manage or learn. A separate license is required. -{{< /tip >}} +- **High Availability and Monitoring**: Comprehensive health checks, metrics collection, + alerting, and automatic failover mechanisms ensure your data platform stays operational. + Real-time monitoring dashboards provide visibility into cluster performance, + resource utilization, and query patterns. + +- **APIs, Drivers and Connectors**: Comprehensive programmatic access through + RESTful APIs, native drivers for popular programming languages (Java, Python, + JavaScript, Go, PHP, and more), and connectors for data integration tools + and BI platforms. + +- **Centralized Orchestration and Resource Management**: Unified control plane + for managing all platform resources, deployments, and configurations. + Kubernetes-powered orchestration handles scaling, updates, and resource + allocation automatically across all components. + +These enterprise features are orchestrated through Kubernetes and the ArangoDB +Kubernetes Operator, providing automated management and enterprise-grade reliability. \ No newline at end of file diff --git a/site/content/data-platform/get-started.md b/site/content/data-platform/get-started.md index f59466e2db..dbe94f2ff2 100644 --- a/site/content/data-platform/get-started.md +++ b/site/content/data-platform/get-started.md @@ -21,10 +21,9 @@ of the platform features. ## Use the Arango Data Platform as a managed service -The Arango Data Platform is not available as a managed service yet, but it will -become available for the [Arango Managed Platform (AMP)](../../amp/_index.md) -in the future. Until then, you can request early access to the self-hosted -Arango Data Platform for testing. +You can request the Arango Data Platform as a managed service for the +[Arango Managed Platform (AMP)](../../amp/_index.md). +[Get in touch](https://arango.ai/contact-us/) with the Arango team to learn more. ## Self-host the Arango Data Platform diff --git a/site/content/data-platform/kubernetes.md b/site/content/data-platform/kubernetes.md new file mode 100644 index 0000000000..e58769feef --- /dev/null +++ b/site/content/data-platform/kubernetes.md @@ -0,0 +1,81 @@ +--- +title: Kubernetes-Native Architecture +menuTitle: Kubernetes +weight: 15 +description: >- + The Arango Data Platform is purpose-built for Kubernetes, leveraging + container orchestration for automated deployment, scaling, and management +--- +The Arango Data Platform is **Kubernetes-native** by design, meaning it is built +from the ground up to run on [Kubernetes](https://kubernetes.io/) and requires +it to function. This is not an optional feature, Kubernetes is the foundation +that powers the entire platform architecture. + +{{< info >}} +**Kubernetes Required**: The Arango Data Platform cannot operate without Kubernetes. +It relies on Kubernetes orchestration and the +[ArangoDB Kubernetes Operator](https://arangodb.github.io/kube-arangodb/) for +all deployment, scaling, and management operations. +{{< /info >}} + +## Why Kubernetes? + +By building exclusively on Kubernetes, the Arango Data Platform delivers +enterprise-grade capabilities that would be difficult or impossible to achieve +with traditional deployment approaches: + +- **Automated Management and Self-Healing**: Kubernetes handles deployment, + scaling, node failures, and rolling updates automatically, with self-healing + capabilities that restart failed containers and maintain high availability + without manual intervention. + +- **Dynamic Scalability and Resource Optimization**: Scale your database cluster + up or down based on workload demands, with efficient resource allocation and + scheduling ensuring optimal utilization of CPU, memory, and storage. + +- **Declarative Configuration and Zero-Downtime Updates**: Define your desired + state using Kubernetes manifests and deploy updates with zero downtime through + controlled rolling updates and easy rollback capabilities. + +- **Cloud and On-Premises Flexibility**: Run on any Kubernetes-compatible + environment—public cloud providers (AWS, Azure, GCP), private cloud, or + on-premises infrastructure—with consistent deployment across all environments. + +## The ArangoDB Kubernetes Operator + +The Arango Data Platform is powered by the official +[ArangoDB Kubernetes Operator](https://arangodb.github.io/kube-arangodb/) +(`kube-arangodb`), which provides the following features: + +- **Custom Resource Definitions (CRDs)**: Extend Kubernetes with ArangoDB-specific + resources like `ArangoDeployment`, `ArangoBackup`, and more. + +- **Intelligent Orchestration**: The operator understands ArangoDB's architecture + and requirements, ensuring deployments follow best practices automatically. + +- **Backup and Restore**: Automated backup management integrated directly into + the Kubernetes workflow. + +- **High Availability**: Built-in support for multi-datacenter replication, + automatic failover, and disaster recovery scenarios. + +- **Enterprise Features**: Full support for ArangoDB Enterprise Edition features + including encryption, auditing, and advanced security controls. + +For detailed information about the operator, see the +[ArangoDB Kubernetes Operator documentation](https://arangodb.github.io/kube-arangodb/docs/). + +## Platform Services as Kubernetes Resources + +All components of the Arango Data Platform, from the core database to the optional +AI Suite, are deployed and managed as native Kubernetes resources. This +means you can do the following: + +- Use standard Kubernetes tools (`kubectl`, Helm, etc.) to manage your deployment +- Monitor platform health using Kubernetes-native observability tools +- Integrate with existing Kubernetes infrastructure and workflows +- Apply your organization's Kubernetes policies and security controls + +This Kubernetes-native approach ensures the Arango Data Platform fits naturally +into modern cloud-native environments and DevOps practices. +