ArangoDB
Why Choose ArangoDB?
Choosing this is smart if you want a database that does it all without making you juggle multiple tools. ArangoDB’s multi-model approach means you can handle graphs, documents, and key-values all in one place, plus it scales easily as you grow. It’s a solid pick for devs who want power and simplicity together.
ArangoDB is a distributed, free, and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.How do you position yourself against your competitors?ArangoDB doesn’t make you choose between graph, document, vector, key-value, full- text search, or geospatial paradigms. You get it ALL in a single, integrated platform.Imagine stitching together the results from 6 separate queries written in 6 different query languages. This is the developer’s life in the world of competing solutions. AQL, ArangoDB’s unified query language, accesses ALL your data with one query. It’s simple to learn and feels more like coding. No more data integration nightmares.As your data and user base grow, ArangoDB effortlessly scales horizontally to accommodate. While competing solutions can only scale vertically (or horizontally with heavy manual intervention), ArangoDB easily scales without any hands-on work by operators. Data is automatically and intelligently distributed across nodes in a lights-out fashion. No unnecessary downtime to manually distribute data. Higher performance from fewer network hops.The result? Far lower TCO, increased operational efficiency, and more satisfied users and customers.
ArangoDB Introduction
What is ArangoDB?
ArangoDB is the company behind the leading, multi-model graph data and analytics platform that uncovers insights that are difficult or impossible with traditional SQL, Document, or even legacy graph databases – making it easier to drive value from connected data faster. ArangoDB now leads the way for Graph-Powered GenAI, Graph Analytics, and GraphML deployed via the most scalable and performant multi-model data architecture leveraged by thousands of Fortune 500 enterprises and innovative startups across many different industries, including financial services, healthcare, and telecommunications. Founded in 2015 in Cologne, Germany, ArangoDB Inc. is a venture-backed, next-generation graph data and analytics company headquartered in San Francisco, California, with offices and employees worldwide. Learn more at www.arangodb.com.
How to use ArangoDB?
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Why Choose ArangoDB?
Choosing this is smart if you want a database that does it all without making you juggle multiple tools. ArangoDB’s multi-model approach means you can handle graphs, documents, and key-values all in one place, plus it scales easily as you grow. It’s a solid pick for devs who want power and simplicity together.
ArangoDB Features
Security
- ✓Role-Based Authorization
- ✓Authentication
- ✓Encryption
Data Management
- ✓Data Model
- ✓Data Types
- ✓Built - In Search
- ✓Data Model
- ✓Data Types
- ✓Built - In Search
- ✓Query Language
Support
- ✓Multi-Model
- ✓Multi-Model
- ✓Operating Systems
Performance
- ✓Query Optimization
- ✓Query Optimization
Pricing
ArangoGraph Insights Platform
The managed service for ArangoDB provides fully-hosted, managed, & monitored cluster deployments of any size, with enterprise-grade security. rices depend on selected cloud provider, region, disk & CPU size.
- ✓ Fully Managed: ArangoDB Oasis offers a fully-managed graph database, document store and full-text search engine. All in one place
- ✓ Highly Secure: Encryption at transit & at rest guarantee all your data is encrypted before it hits the disk or send over the network. In addition, you can assign fine-grained access control policies to your organization, your projects or deployments. This assigns permissions to groups or individual users
- ✓ Elastic Scale: You can elastically scale with all deployment models (OneShard & Sharded Clusters) at anytime and use the special Enterprise features for efficient queries against distributed data