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Full Geospatial

Unlock the Power of Location: ArangoDB's Full Geospatial Capabilities Enhance Your Data Queries with Precise Spatial Context, All in Real-Time

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“We needed a data store that met the performance requirements, but more importantly we wanted to test a new approach to save on the development side. We needed graphs to go with the recommendations presented to users, but also common join operations as well as a database for storing and processing of geo data.”

– Alex Pavlov, IT Solutions Architect
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Get started with
Graph today

(no credit card required), and experience the shortest time to value for a hosted graph DB.

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Read the
Case Studies

Learn why companies across industries are switching to ArangoDB for Graph.

Real-Time Spatial Queries

Machine learning done right

With

Consider a logistics example: ArangoDB's real-time spatial queries empower fleet management systems to instantly calculate optimal routes based on real-time traffic data, vehicle locations, and delivery windows, thereby reducing operational costs and improving delivery efficiency.

Why it Matters: Real-time spatial queries in fleet management directly impact the bottom line by optimizing fuel consumption and minimizing delays. This enhanced efficiency translates to cost savings, happier customers, and a more sustainable operation.

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Without

In contrast, a legacy graph database would struggle with real-time route optimization, often requiring separate geospatial services or manual calculations. This leads to slower response times, increased operational complexity, and potentially higher costs for fleet management.

KEY QUESTION: Do you require the capability to perform real-time spatial queries that can adapt to changing conditions, for example traffic and vehicle availability, and how will this impact your operational efficiency and costs?

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Rich Geospatial Functions

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With

Advanced geospatial capabilities empower retailers to analyze real-time consumer foot traffic within physical stores.

These functions include GEO_DISTANCE, GEO_CONTAINS, GEO_INTERSECTS, GEO_NEAREST, GEO_WITHIN_RECTANGLE, and many others.

WHY IT MATTERS: Retailers are now equipped to adapt store conditions on the fly, thereby significantly enhancing customer experiences and informed decision-making processes.

There are similar applications for many other industries.

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Legacy Graph Databases typically lag behind in offering robust geospatial functions natively. While some basic spatial queries might be possible, they often require additional layers or third-party integrations to achieve similar functionality.

This can result in increased complexity and latency, affecting the real-time capabilities essential for certain applications.

KEY QUESTION: What current geospatial requirements do your applications have, and what might they be in the future? What is the value of having this native support out-of-the-box within your Graph DB?

GeoJSON Support

Machine learning done right

With

ArangoDB's native GeoJSON support allows industries like environmental monitoring to effortlessly map, analyze, and visualize complex geographical data right within the database.

ArangoDB integrates GeoJSON as a first-class citizen, enabling intricate queries without additional tools or plugins.

WHY IT MATTERS: GeoJSON support eliminates the need for data conversion or additional software, streamlining workflows.

This efficiency is crucial for applications where real-time geographic data can be a matter of public safety or environmental conservation

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In most cases, Legacy Graph Databases lack native GeoJSON support, forcing organizations to rely on external libraries or services for geospatial analysis. This creates additional layers of complexity, affecting real-time data processing and increasing the risk of errors.

Without GeoJSON, users might have to resort to less efficient means of conducting spatial queries, often requiring convoluted workarounds that can result in slower query performance.

KEY QUESTIONS: What would be your required workarounds without native, in-built GeoJSON support? Also, how would your real-time analytic requirements and performance SLAs be compromised without it?"

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Advanced Spatial Aggregation

Machine learning done right

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ArangoDB's Advanced Spatial Aggregation support allows for high-complexity geospatial analyses right within the database.

Users can perform real-time calculations on spatial data, like calculating centroids or aggregating multiple geographic boundaries, without exporting data or using third-party tools.

WHY IT MATTERS: This capability empowers businesses to make quicker, data-driven decisions directly affecting operational efficiency and customer experience. In sectors like urban planning or natural resource management, real-time geospatial insights can make a substantial impact.

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Without

Many legacy graph databases lack native support for advanced spatial aggregation, forcing organizations to rely on separate geospatial databases or third-party analytical tools.

This disjointed approach results in increased complexity, latency, and risk of data inconsistency. In most cases, the database may offer only basic geospatial capabilities, lacking the real-time analytical prowess needed for
complex calculations and aggregations.

KEY QUESTION: How much time, effort, and additional technology would it take you to perform complex spatial analyses, and what is the opportunity cost of that?

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Get started with
Graph today

(no credit card required), and experience the shortest time to value for a hosted graph DB.

get started icon v2

Read the
Case Studies

Learn why companies across industries are switching to ArangoDB for Graph.

Get Started With ArangoGraph

Experience the shortest time to value for a hosted graph DB (no credit card required).