Product Name: ArangoDB
Company Name: ArangoDB GmbH
URL: https://www.arangodb.com
Entry Year: 2012

Market Share (or Graph DB Revenue):
ArangoDB is a recognized player in the multi-model database market, supporting graph, document, and key-value data models. Exact market share or revenue is not publicly available, but ArangoDB has a significant user base, particularly among startups and enterprises leveraging multi-model databases.

Number of Employees: Approximately 100-150 employees

Capital: Not publicly disclosed

Funding:
ArangoDB has raised about $17 million in funding through multiple rounds, with the most recent Series A round raising $10 million in April 2019. Key investors include Bow Capital, Target Partners, and Iris Capital.

Major Users:
ArangoDB’s clients include major organizations like Airbus, Barclays, Cisco, Thomson Reuters, and NVIDIA. It is also popular among tech startups and companies seeking flexible data models for complex applications.

Key Application Areas:
ArangoDB is used in a variety of fields including fraud detection, knowledge graphs, social network analysis, recommendation engines, IoT analytics, and content management systems.

Product Overview:
ArangoDB is a multi-model database that supports graph, document, and key-value store models, allowing for more flexibility in data storage and retrieval. It provides native graph database capabilities and is optimized for highly scalable, complex queries across different data models. ArangoDB’s multi-model approach helps enterprises handle mixed workloads without the need for multiple databases.

Data Compatibility:
ArangoDB supports a variety of data formats, including JSON, CSV, XML, and integrates with other systems via RESTful APIs, GraphQL, and Apache Kafka. Its multi-model nature allows it to work with multiple types of data without converting between different formats.

Knowledge Graph Implementation:
ArangoDB can build knowledge graphs using its native graph model. It allows users to link entities and relationships flexibly and provides extensive querying capabilities for analyzing and visualizing data relationships. The knowledge graph is often combined with document data for richer context.

Query Method:
ArangoDB uses AQL (ArangoDB Query Language), a declarative query language that supports graph traversal and is optimized for querying across its different data models (graph, document, and key-value). AQL is highly expressive and supports complex queries spanning multiple datasets.

Natural Language Queries:
ArangoDB does not natively support natural language querying, but it can be integrated with third-party NLP tools to interpret and translate natural language inputs into AQL queries for specialized applications.

Native Machine Learning:
ArangoDB does not offer a built-in graph-based machine learning library, but its ArangoML pipeline can be used to manage and store machine learning features and results, especially when combined with graph models. It supports integration with external ML frameworks for managing the ML lifecycle within the database.

Support for Traditional Machine Learning:
ArangoDB provides integrations with popular ML platforms like TensorFlow and scikit-learn, allowing users to extract features from graph or document data and use them in traditional machine learning models. It also supports ArangoML Pipeline, an open-source project for managing ML metadata.

Support for LLMs:
ArangoDB has emerging use cases for integrating with large language models (LLMs) to enhance graph-based analytics and natural language understanding. While not a native feature, users can integrate LLMs for advanced text and graph processing tasks.

Support for RAG (Retrieval-Augmented Generation):
ArangoDB’s fast graph traversal and querying capabilities can be utilized in RAG models by providing relevant data retrieval from its knowledge graph to augment and enhance the quality of text generated by large language models, especially for real-time applications.

Other Notable Features:

• Multi-model database: ArangoDB’s multi-model approach allows users to store and query graph, document, and key-value data natively, providing flexibility for complex applications.
• Foxx Microservices: ArangoDB includes Foxx, a framework for building microservices directly within the database, allowing developers to create REST APIs that interact with the database without additional layers.
• ArangoDB Oasis: A fully managed, cloud-hosted version of ArangoDB available on major platforms like AWS, Google Cloud, and Microsoft Azure.
• High Availability and Scaling: ArangoDB supports sharding, replication, and clustering, ensuring high availability and scalability for enterprise workloads.
• Security: Role-based access control, TLS/SSL encryption, and support for enterprise-level authentication systems ensure secure database operations.