Graph + Document
Empowering Versatile Data Management: ArangoDB's Graph + Document Capability Seamlessly Combines Graph and Document Data Models, Boosting Flexibility and Efficiency.
"Now, my default go to is going to be ArangoDB. Certainly for key/value information, for document, for graph. And I'm looking at some of the Neo4j projects I've done in the past and I might convert them."
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Graph today
(no credit card required), and experience the shortest time to value for a hosted graph DB.
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Case Studies
Learn why companies across industries are switching to ArangoDB for Graph.
Unified Insights
With
In the healthcare sector, ArangoDB's amalgamation of graph and document data underpins Unified Insights.
Picture a hospital utilizing ArangoDB to seamlessly combine patient records (documents) with intricate medical relationships (graphs).
When a physician requires a comprehensive patient overview, ArangoDB's unified query language effortlessly retrieves structured records and intricate relationships, fostering holistic insights. This synergy facilitates accurate diagnoses and well-informed treatment strategies.
Without
Let’s look at how the world would be with legacy graph databases in the same medical scenario.
To try and get unified insights, you’d have to duplicate patient records into a separate document database. This results in data redundancy, intricate querying processes across multiple databases, and integration complexities.
Inconsistent views, sluggish query performance, scalability challenges, and increased resource usage further complicate the process.
These limitations would threaten the hospital's ability to efficiently combine graph and document data, hampering comprehensive insights for informed medical decisions.
Streamlined Operations
With
In the logistics sector, ArangoDB's fusion of graph and document data streamlines operations.
Imagine a supply chain management company using ArangoDB to integrate shipment data (documents) with intricate logistics networks (graphs). When optimizing routes and deliveries, ArangoDB's unified query language seamlessly retrieves both structured records and complex relationships.
There's ZERO lag in bringing this data together, allowing real-time decision making. The result? Optimized logistics.
Without
In the logistics context, where managing logistics networks (graphs) and shipment records (documents) is vital, a complex process unfolds.
Duplicating data into a separate document database is required, leading to data redundancy, intricate queries, integration complexities, inconsistent views, compromised performance, scaling problems, and resource consumption. The complexity arises from the need for more code to join data from separate databases, significantly increasing query complexity and maintenance efforts. This complicated process hampers the efficiency of operational tasks in logistics, setting modern solutions like ArangoDB apart.
More Powerful Graphs
With
ArangoDB's more powerful graph functionality is evident in the retail industry. Imagine an e-commerce platform that needs to very quickly analyze website behavior of customers for real-time and customized offers.
ArangoDB's advanced graph traversal, smart indexing, and schema flexibility allow retailers to more quickly uncover intricate customer behavior patterns, such as identifying clusters of high-spending customers with similar interests.
For example, ArangoDB has the ability to perform “multi-hop” traversals efficiently. ArangoDB's graph traversal capabilities allow for traversing multiple relationships in a single query, minimizing the need for intermediate queries or complex logic.
Without
Legacy graph databases often require developers to perform multiple queries or implement intricate logic to achieve similar results. Think of this as “manual multi-hops” which is very inefficient and tedious, significantly delaying the whole process.
Not to mention, query complexity, resource consumption, and development effort are also all increased with legacy graph databases, resulting in much higher TCO.
Schema inflexibility is another problem. Let’s say you have a new promotion that requires new data and different sets of user info. The requirement to manually modify schemas to accommodate new data will slow the promotion’s rollout.
Enhanced Customer Experience
With
In the realm of retail, ArangoDB's fusion of graph and document data brings enhanced customer experiences. Visualize an e-commerce hub employing ArangoDB to handle product details (documents) and customer connections (graphs).
With ArangoDB's unified query language, the platform efficiently examines intricate customer interactions, tailors product suggestions, and pinpoints influential buyers.
ArangoDB's advanced graph capabilities effortlessly unite varied data formats, ushering in comprehensive insights that fuel personalized shopping journeys and transform retail interactions.
Without
The customer's perspective in this retail scenario would be marked by frustration and confusion when the legacy graph database is unable to seamlessly integrate graph and document data.
Why? As customers navigate the e-commerce platform, they might notice disjointed product recommendations that fail to resonate with their preferences. Inconsistent suggestions and disjointed information about products could leave them feeling unsatisfied and overwhelmed.
Inefficient querying is the culprit, leading to a lack of trust in the platform's understanding of their preferences, ultimately impacting their overall shopping satisfaction and loyalty.
Get started with
Graph today
(no credit card required), and experience the shortest time to value for a hosted graph DB.
Read the
Case Studies
Learn why companies across industries are switching to ArangoDB for Graph.