From 94968f393507453e0e2bf86ed35a5d254e4a3450 Mon Sep 17 00:00:00 2001 From: Simran Spiller Date: Wed, 29 Oct 2025 13:21:39 +0100 Subject: [PATCH 1/4] WIP: Docs homepage content Reuses the Graph to AI page --- .../{ai-suite/graph-to-ai.md => _index.md} | 73 ++++++++++++------- site/content/ai-suite/_index.md | 6 ++ site/content/images/avo-core.svg | 6 ++ site/content/images/avo-full.svg | 6 ++ site/content/images/avo-middle.svg | 6 ++ 5 files changed, 70 insertions(+), 27 deletions(-) rename site/content/{ai-suite/graph-to-ai.md => _index.md} (69%) create mode 100644 site/content/images/avo-core.svg create mode 100644 site/content/images/avo-full.svg create mode 100644 site/content/images/avo-middle.svg diff --git a/site/content/ai-suite/graph-to-ai.md b/site/content/_index.md similarity index 69% rename from site/content/ai-suite/graph-to-ai.md rename to site/content/_index.md index f5a4730563..ffee95cdfd 100644 --- a/site/content/ai-suite/graph-to-ai.md +++ b/site/content/_index.md @@ -1,20 +1,39 @@ --- -title: From Graph to AI -menuTitle: From Graph to AI -weight: 25 +title: Arango Documentation +menuTitle: Home +weight: 1 description: >- - ArangoDB's set of tools and technologies enables analytics, machine learning, - and AI applications powered by graph data -aliases: - - data-science/overview + Arango provides the trusted data foundation for the next wave of AI grounded + in business context +#aliases: +# - data-science/overview --- +## Product documentation -{{< tip >}} -The Arango Data Platform & AI Suite are available as a pre-release. To get -exclusive early access, [get in touch](https://arango.ai/contact-us/) with -the Arango team. -{{< /tip >}} +{{< cards >}} +{{% card title="Arango Data Platform" link="data-platform/" %}} +The enterprise foundation built on ArangoDB, with platform services for +scalability, reliability, governance, and a graph exploration tool. +{{% /card %}} + +{{% card title="AI Suite" link="ai-suite/" %}} +Supercharge your Data Platform with Hybrid/GraphRAG, GraphML, advanced analytics, +and queries generated from natural language for AI-powered data insights. +{{% /card %}} + +{{% card title="ArangoDB" link="arangodb/" %}} +A native graph multi-model database system that unifies graph, document, +key-value, vector, and full-text search in one engine with one query language. +{{% /card %}} + +{{% card title="Arango Managed Platform (AMP)" link="amp/" %}} +Arango's fully-managed cloud offering for a faster time to value. +{{% /card %}} + +{{< /cards >}} + + +![The outlines of the Arango avocado logo but the seed has a fill color](images/avo-core.svg) + +![The Arango avocado logo with the seed and surrounding flesh with a fill color](images/avo-middle.svg) + +![The Arango avocado logo with the seed, flesh, and outer layer having a fill color](images/avo-full.svg) + ## From graph to AI This section classifies the complexity of the queries you can answer with @@ -50,9 +75,9 @@ Graph queries can also determine the shortest paths between nodes. Graph queries can answer questions like _**Who can introduce me to person X**_? -![Graph Query](../images/graph-query.png) +![Graph Query](images/graph-query.png) -See [Graphs in AQL](../arangodb/3.12/aql/graphs/_index.md) for the supported graph queries. +See [Graphs in AQL](arangodb/3.12/aql/graphs/_index.md) for the supported graph queries. ### Graph Analytics @@ -61,12 +86,12 @@ know aggregate information about your graph, while analyzing the entire graph. Graph analytics can answer questions like _**Who are the most connected persons**_? -![Graph Analytics](../images/graph-analytics.png) +![Graph Analytics](images/graph-analytics.png) ArangoDB offers _Graph Analytics Engines_ to run algorithms such as connected components, label propagation, and PageRank on your data. This feature -is available for the Arango Managed Platform (AMP). See -[Graph Analytics](graph-analytics.md) for details. +is available in the AI Data Platform and the Arango Managed Platform (AMP). See +[Graph Analytics](ai-suite/graph-analytics.md) for details. ### GraphML @@ -78,10 +103,10 @@ GraphML can answer questions like: - _**Will a customer churn?**_ - _**Is this particular transaction Anomalous?**_ -![Graph ML](../images/graph-ml.png) +![Graph ML](images/graph-ml.png) For ArangoDB's enterprise-ready, graph-powered machine learning offering, -see [Arango GraphML](graphml/_index.md). +see [Arango GraphML](ai-suite/graphml/_index.md). ### GraphRAG @@ -102,7 +127,7 @@ The overall process of GraphRAG involves the following: to augment responses using both structured and unstructured data, providing accurate responses with the desired format and degree of detail for each query. -To learn more, see the [GraphRAG](graphrag/_index.md) documentation. +To learn more, see the [GraphRAG](ai-suite/graphrag/_index.md) documentation. ## Knowledge Graphs @@ -124,9 +149,3 @@ the following tasks: - Coreference resolution - End-to-end knowledge graph construction - (Text) Embeddings - -## Sample datasets - -If you want to try out ArangoDB's data science features, you may use the -[`arango-datasets` Python package](../arangodb/3.12/components/tools/arango-datasets.md) -to load sample datasets into a deployment. diff --git a/site/content/ai-suite/_index.md b/site/content/ai-suite/_index.md index c149b1fea4..4f23bcaa4c 100644 --- a/site/content/ai-suite/_index.md +++ b/site/content/ai-suite/_index.md @@ -37,3 +37,9 @@ Alongside these components, you also get the following additional features: AI Suite and build your own integrations. See the [Protocol Documentation](https://arangoml.github.io/platform-dss-api/GenAI-Service/proto/index.html) for more details. + +## Sample datasets + +If you want to try out ArangoDB's data science features, you may use the +[`arango-datasets` Python package](../arangodb/3.12/components/tools/arango-datasets.md) +to load sample datasets into a deployment. \ No newline at end of file diff --git a/site/content/images/avo-core.svg b/site/content/images/avo-core.svg new file mode 100644 index 0000000000..5d7bc8c7ab --- /dev/null +++ b/site/content/images/avo-core.svg @@ -0,0 +1,6 @@ + + + + + + diff --git a/site/content/images/avo-full.svg b/site/content/images/avo-full.svg new file mode 100644 index 0000000000..0e11a25947 --- /dev/null +++ b/site/content/images/avo-full.svg @@ -0,0 +1,6 @@ + + + + + + diff --git a/site/content/images/avo-middle.svg b/site/content/images/avo-middle.svg new file mode 100644 index 0000000000..00c9d91cbd --- /dev/null +++ b/site/content/images/avo-middle.svg @@ -0,0 +1,6 @@ + + + + + + From b8a6803674547831b42fd9d9c15cea0ee01049bf Mon Sep 17 00:00:00 2001 From: Paula Date: Tue, 4 Nov 2025 10:12:35 +0100 Subject: [PATCH 2/4] add avocado icons to product cards, remove old images --- site/content/_index.md | 28 ++++++++-------------------- 1 file changed, 8 insertions(+), 20 deletions(-) diff --git a/site/content/_index.md b/site/content/_index.md index ffee95cdfd..491cf10d8d 100644 --- a/site/content/_index.md +++ b/site/content/_index.md @@ -12,19 +12,18 @@ description: >- {{< cards >}} -{{% card title="Arango Data Platform" link="data-platform/" %}} -The enterprise foundation built on ArangoDB, with platform services for -scalability, reliability, governance, and a graph exploration tool. +{{% card title="ArangoDB" link="arangodb/" %}} +![](images/avo-core.svg) Graph multi-model database system that unifies graph, document, +key-value, vector, and full-text search with one query language. {{% /card %}} -{{% card title="AI Suite" link="ai-suite/" %}} -Supercharge your Data Platform with Hybrid/GraphRAG, GraphML, advanced analytics, -and queries generated from natural language for AI-powered data insights. +{{% card title="Arango Data Platform" link="data-platform/" %}} +![](images/avo-middle.svg) Adds platform services for scalability, reliability, governance, and a graph exploration tool. {{% /card %}} -{{% card title="ArangoDB" link="arangodb/" %}} -A native graph multi-model database system that unifies graph, document, -key-value, vector, and full-text search in one engine with one query language. +{{% card title="AI Suite" link="ai-suite/" %}} +![](images/avo-full.svg) Supercharge your Data Platform with GraphRAG, GraphML, +and queries generated from natural language for AI-powered insights. {{% /card %}} {{% card title="Arango Managed Platform (AMP)" link="amp/" %}} @@ -51,11 +50,6 @@ engineering space can make use of ArangoDB's set of tools and technologies that enable analytics and machine learning on graph data. --> -![The outlines of the Arango avocado logo but the seed has a fill color](images/avo-core.svg) - -![The Arango avocado logo with the seed and surrounding flesh with a fill color](images/avo-middle.svg) - -![The Arango avocado logo with the seed, flesh, and outer layer having a fill color](images/avo-full.svg) ## From graph to AI @@ -75,8 +69,6 @@ Graph queries can also determine the shortest paths between nodes. Graph queries can answer questions like _**Who can introduce me to person X**_? -![Graph Query](images/graph-query.png) - See [Graphs in AQL](arangodb/3.12/aql/graphs/_index.md) for the supported graph queries. ### Graph Analytics @@ -86,8 +78,6 @@ know aggregate information about your graph, while analyzing the entire graph. Graph analytics can answer questions like _**Who are the most connected persons**_? -![Graph Analytics](images/graph-analytics.png) - ArangoDB offers _Graph Analytics Engines_ to run algorithms such as connected components, label propagation, and PageRank on your data. This feature is available in the AI Data Platform and the Arango Managed Platform (AMP). See @@ -103,8 +93,6 @@ GraphML can answer questions like: - _**Will a customer churn?**_ - _**Is this particular transaction Anomalous?**_ -![Graph ML](images/graph-ml.png) - For ArangoDB's enterprise-ready, graph-powered machine learning offering, see [Arango GraphML](ai-suite/graphml/_index.md). From 3fde7f025231e3d6df4ad3d0a188ff4e0bb9922e Mon Sep 17 00:00:00 2001 From: Simran Spiller Date: Tue, 4 Nov 2025 13:29:54 +0100 Subject: [PATCH 3/4] Adjust card CSS to float an icon to the right of the title --- .../arangodb-docs-theme/static/css/theme.css | 14 +++----------- 1 file changed, 3 insertions(+), 11 deletions(-) diff --git a/site/themes/arangodb-docs-theme/static/css/theme.css b/site/themes/arangodb-docs-theme/static/css/theme.css index 1dd47fc6ef..8eeed2df74 100644 --- a/site/themes/arangodb-docs-theme/static/css/theme.css +++ b/site/themes/arangodb-docs-theme/static/css/theme.css @@ -478,24 +478,16 @@ a.section-link { } .card-head { - position: relative; z-index: 2; - display: flex; margin-bottom: 10px; - flex-flow: column; min-height: 40px; - justify-content: center; - align-items: flex-start; } .card-icon { - width: 40px; - height: 40px; - -o-object-fit: contain; + width: 30px; object-fit: contain; - position: absolute; - top: 0; - left: 0; + float: right; + margin-left: 10px; } .card-title { From fb529aabf00ef284238abae75c9f1e225b9a193f Mon Sep 17 00:00:00 2001 From: Simran Spiller Date: Tue, 4 Nov 2025 16:22:51 +0100 Subject: [PATCH 4/4] Rework homepage and ArangoDB introduction - New and reworked sections for From Graph to AI for a full journey - Move knowledge graph definition to GraphRAG - Remove outdated ArangoDB diagram from overview and mention self-managed cloud deployments - Use card shortcode icon parameter --- site/content/_index.md | 157 ++++++++++------------- site/content/ai-suite/graphrag/_index.md | 52 +++++--- site/content/arangodb/_index.md | 10 +- 3 files changed, 107 insertions(+), 112 deletions(-) diff --git a/site/content/_index.md b/site/content/_index.md index 491cf10d8d..b95a8b3a4e 100644 --- a/site/content/_index.md +++ b/site/content/_index.md @@ -8,132 +8,109 @@ description: >- #aliases: # - data-science/overview --- -## Product documentation +## User manuals by product {{< cards >}} -{{% card title="ArangoDB" link="arangodb/" %}} -![](images/avo-core.svg) Graph multi-model database system that unifies graph, document, +{{% card title="ArangoDB" link="arangodb/" icon="avo-core.svg" %}} +Native multi-model database system that unifies graph, document, key-value, vector, and full-text search with one query language. {{% /card %}} -{{% card title="Arango Data Platform" link="data-platform/" %}} -![](images/avo-middle.svg) Adds platform services for scalability, reliability, governance, and a graph exploration tool. +{{% card title="Arango Data Platform" link="data-platform/" icon="avo-middle.svg" %}} +Adds platform services for scalability, reliability, governance, and a graph exploration tool. {{% /card %}} -{{% card title="AI Suite" link="ai-suite/" %}} -![](images/avo-full.svg) Supercharge your Data Platform with GraphRAG, GraphML, +{{% card title="AI Suite" link="ai-suite/" icon="avo-full.svg" %}} +Supercharge your Data Platform with GraphRAG, GraphML, and queries generated from natural language for AI-powered insights. {{% /card %}} {{% card title="Arango Managed Platform (AMP)" link="amp/" %}} -Arango's fully-managed cloud offering for a faster time to value. +Arango's fully-managed cloud offering for a faster time to value, +formerly known as ArangoGraph Insights Platform. {{% /card %}} {{< /cards >}} - +ArangoDB is a scalable database system that you can use to store +[JSON documents](arangodb/3.12/concepts/data-structure/documents/_index.md), +which allows a flexible data structure for each record. ArangoDB natively supports +[graphs](arangodb/3.12/graphs/_index.md), letting you connect documents with +edges to express relationships between records and build complex +information networks. +### Data Retrieval -## From graph to AI +You can query your data in various ways using the core database system. +The native support for multiple data models lets you access information in +different ways with a single query language called [AQL](arangodb/3.12/aql/_index.md). +It has built-in support for aggregation, vector and full-text search, geo-spatial +queries, and more. -This section classifies the complexity of the queries you can answer with -ArangoDB and gives you an overview of the respective feature. +### Data Exploration -It starts with running a simple query that shows what is the path that goes from -one node to another, continues with more complex tasks like graph classification, -link prediction, and node classification, and ends with generative AI solutions -powered by graph relationships and vector embeddings. +You can visually explore and interact with your ArangoDB graphs through an +intuitive web interface called the [Graph Visualizer](data-platform/graph-visualizer.md). +It is part of the [Arango Data Platform](data-platform/_index.md) that builds on +ArangoDB, extending it to a Kubernetes-native environment that unifies +data management, monitoring, and automation. ### Graph Queries -When you run an AQL query on a graph, a traversal query can go from a node to -multiple edges, and then the edges indicate what the next connected nodes are. -Graph queries can also determine the shortest paths between nodes. - -Graph queries can answer questions like _**Who can introduce me to person X**_? - -See [Graphs in AQL](arangodb/3.12/aql/graphs/_index.md) for the supported graph queries. +Utilizing connected data starts with running simple [graph queries](arangodb/3.12/aql/graphs/_index.md). +Using ArangoDB and its query language, you can determine the shortest paths between nodes as well as execute graph traversals. A traversal starts at a +given node of a graph and follows the directly connected edges. The edges indicate +what the next connected nodes are, and this discovery of neighbors can repeat. + +Graph queries can answer questions like **Who can introduce me to person X?** ### Graph Analytics -Graph analytics or graph algorithms is what you run on a graph if you want to -know aggregate information about your graph, while analyzing the entire graph. +The next level of utilizing connected data in terms of complexity is to use +graph analytics or graph algorithms to aggregate information about a graph. +Unlike with graph queries, this involves the entire graph at once. -Graph analytics can answer questions like _**Who are the most connected persons**_? +Graph analytics can answer questions like **Who are the most connected persons?** -ArangoDB offers _Graph Analytics Engines_ to run algorithms such as -connected components, label propagation, and PageRank on your data. This feature -is available in the AI Data Platform and the Arango Managed Platform (AMP). See -[Graph Analytics](ai-suite/graph-analytics.md) for details. +Arango offers a [Graph Analytics](ai-suite/graph-analytics.md) solution as part +of the [Arango AI Data Platform](data-platform/features.md) to run algorithms +such as connected components, label propagation, and PageRank on your data. ### GraphML -When applying machine learning on a graph, you can predict connections, get -better product recommendations, and also classify nodes, edges, and graphs. +For higher-level insights, you can use advanced graph-based data science. +Applying machine learning on graphs lets you predict connections, get better +product recommendations, and also classify nodes, edges, and graphs. GraphML can answer questions like: -- _**Is there a connection between person X and person Y?**_ -- _**Will a customer churn?**_ -- _**Is this particular transaction Anomalous?**_ +- **Is there a connection between person X and person Y?** +- **Will a customer churn?** +- **Is this particular transaction anomalous?** -For ArangoDB's enterprise-ready, graph-powered machine learning offering, -see [Arango GraphML](ai-suite/graphml/_index.md). +Arango's enterprise-ready, graph-powered machine learning capabilities are +included in the [AI Suite](ai-suite/_index.md) as part of the +Arango AI Data Platform. See [Arango GraphML](ai-suite/graphml/_index.md). ### GraphRAG -GraphRAG is ArangoDB's turn-key solution to transform your organization's data into -a knowledge graph and let everyone utilize the knowledge by asking questions in -natural language. - -The overall process of GraphRAG involves the following: -- **Creating a Knowledge Graph** from raw text data. -- **Identifying and extract entities and relationships** within the data. -- **Storing the structured information** in ArangoDB. -- **Clustering each closely connected set of entities into semantic contexts** - via topology-based algorithms and summarization. -- **Using such semantically augmented structured representation** as the - foundation for efficient and accurate information retrieval via lexical and - semantic search. -- **Integrating retrieval methods with LLMs (privately or publicly hosted)** - to augment responses using both structured and unstructured data, providing - accurate responses with the desired format and degree of detail for each query. - -To learn more, see the [GraphRAG](ai-suite/graphrag/_index.md) documentation. - -## Knowledge Graphs - -A knowledge graph can be thought of as a dynamic and interconnected network of -real-world entities and the intricate relationships that exist between them. - -Key aspects of knowledge graphs: -- **Domain-specific knowledge**: You can tailor knowledge graphs to specific - domains and industries. -- **Structured information**: Makes it easy to query, analyze, and extract - meaningful insights from your data. -- **Accessibility**: You can build a Semantic Web knowledge graph or using - custom data. - -LLMs can help distill knowledge graphs from natural language by performing -the following tasks: -- Entity discovery -- Relation extraction -- Coreference resolution -- End-to-end knowledge graph construction -- (Text) Embeddings +Generative AI often struggle with hallucinations because the connectedness of +data is not properly or cleanly represented. GraphRAG is a technique that +turbocharges GenAI applications using the power of graph relationships and +vector embeddings. + +Arango's [GraphRAG](ai-suite/graphrag/_index.md) included in the +[AI Suite](ai-suite/_index.md) is a turn-key solution to transform your +organization's data into a knowledge graph and let everyone utilize the +knowledge by asking questions in natural language. + +It automatically creates a knowledge graph from raw text by identifying and +extracting entities and relationships within the data, groups and summarizes +semantically similar entities, and stores everything in ArangoDB. When you ask a +question, the large language model (LLM) is supplied with additional context +from the knowledge graph, using lexical and semantic search. This enables +accurate, context-aware intelligence grounded in enterprise data. diff --git a/site/content/ai-suite/graphrag/_index.md b/site/content/ai-suite/graphrag/_index.md index b284f820e1..55b66214f3 100644 --- a/site/content/ai-suite/graphrag/_index.md +++ b/site/content/ai-suite/graphrag/_index.md @@ -3,7 +3,7 @@ title: GraphRAG menuTitle: GraphRAG weight: 5 description: >- - ArangoDB's GraphRAG solution combines graph-based retrieval-augmented generation + Arango's GraphRAG solution combines graph-based retrieval-augmented generation with Large Language Models (LLMs) for turbocharged AI solutions aliases: llm-knowledge-graphs @@ -14,9 +14,30 @@ exclusive early access, [get in touch](https://arango.ai/contact-us/) with the Arango team. {{< /tip >}} +## What are knowledge graphs? + +A knowledge graph can be thought of as a dynamic and interconnected network of +real-world entities and the intricate relationships that exist between them. + +Key aspects of knowledge graphs: +- **Domain-specific knowledge**: You can tailor knowledge graphs to specific + domains and industries. +- **Structured information**: Makes it easy to query, analyze, and extract + meaningful insights from your data. +- **Accessibility**: You can build a Semantic Web knowledge graph or using + custom data. + +LLMs can help distill knowledge graphs from natural language by performing +the following tasks: +- Entity discovery +- Relation extraction +- Coreference resolution +- End-to-end knowledge graph construction +- (Text) Embeddings + ## Transform unstructured documents into intelligent knowledge graphs -ArangoDB's GraphRAG solution enables organizations to extract meaningful insights +Arango's GraphRAG solution enables organizations to extract meaningful insights from their document collections by creating knowledge graphs that capture not just individual facts, but the intricate relationships between concepts across documents. This approach goes beyond traditional RAG systems by understanding document @@ -30,23 +51,22 @@ conceptual understanding. ## Key benefits for enterprise applications -- **Cross-document relationship intelligence**: -Unlike traditional RAG systems that treat documents in isolation, ArangoDB's GraphRAG -pipeline detects and leverages references between documents and chunks. This enables -more accurate responses by understanding how concepts relate across your entire knowledge base. - -- **Multi-level understanding architecture**: -The system provides both detailed technical responses and high-level strategic insights -from the same knowledge base, adapting response depth based on query complexity and user intent. +- **Cross-document relationship intelligence**\ + Unlike traditional RAG systems that treat documents in isolation, Arango's GraphRAG + pipeline detects and leverages references between documents and chunks. This enables + more accurate responses by understanding how concepts relate across your entire knowledge base. -- **Reference-aware knowledge graph**: -GraphRAG automatically detects and maps relationships between document chunks while -maintaining context of how information connects across different sources. +- **Multi-level understanding architecture**\ + The system provides both detailed technical responses and high-level strategic insights + from the same knowledge base, adapting response depth based on query complexity and user intent. -- **Dynamic knowledge evolution**: -The system learns and improves understanding as more documents are added, with -relationships and connections becoming more sophisticated over time. +- **Reference-aware knowledge graph**\ + GraphRAG automatically detects and maps relationships between document chunks while + maintaining context of how information connects across different sources. +- **Dynamic knowledge evolution**\ + The system learns and improves understanding as more documents are added, with + relationships and connections becoming more sophisticated over time. ## What's next diff --git a/site/content/arangodb/_index.md b/site/content/arangodb/_index.md index 56103ad6a4..c77041e771 100644 --- a/site/content/arangodb/_index.md +++ b/site/content/arangodb/_index.md @@ -9,15 +9,13 @@ aliases: - introduction - introduction/about-arangodb --- -![ArangoDB Overview Diagram](../images/arangodb-overview-diagram.png) - ArangoDB combines the analytical power of native graphs with an integrated -search engine, JSON support, and a variety of data access patterns via a single, -composable query language. +search engine, JSON support, vector indexes, and a variety of data access +patterns via a single, composable query language. ArangoDB is available in a community and a commercial [edition](3.12/features/_index.md). -You can use it for on-premises deployments, as well as a fully managed -cloud service, the [Arango Managed Platform (AMP)](../amp/_index.md). +You can use it for on-premises deployments, self-managed cloud deployments, +as well as a fully managed cloud service, the [Arango Managed Platform (AMP)](../amp/_index.md). ## What are Graphs?