Drowning in Reality Capture Data? Why Traditional Storage is Failing You
Reality capture data is a powerful asset, until it turns into a liability. Scans pile up across cloud drives and servers, buried in endless folders with no clear way to retrieve, compare, or integrate them. Teams waste hours chasing down the right version, manually stitching together datasets, and fighting with outdated storage systems. It’s an expensive mess. But what if data didn’t have to be scattered and frustrating? What if it were instantly accessible, easy to explore, and seamlessly connected to your workflows?
Written by
Published on
Do not index
Do not index
Drowning in Reality Capture Data? Why Traditional Storage is Failing You
At LumiDB, we’re building a database for reality capture data that will make handling big point cloud datasets easy, accessible and fun. Request access to the alpha version to try our API.
Reality capture data, such as 3D point clouds, is incredibly powerful when first collected, fueling analysis, planning, and project execution. But over time, the way it’s managed turns into madness. Scans get buried in network drives, cloud platforms, and hard disks, making retrieval difficult and limiting their long-term value. Files are mislabeled, buried in obscure folders, and scattered across systems, forcing teams into a wild goose chase just to find the latest version and the data ends up underutilized. This isn’t just frustrating; it slows down critical workflows and costs businesses time and money.
This overwhelming fragmentation is what we call File Chaos, a term I previously explored in a blog post. This challenge affects industries across the board. Airports, general contractors, city planners, mining and energy companies, surveyors, and digital twin developers all rely on massive reality capture datasets—but without a better way to manage them, valuable insights remain locked away in scattered files. But what if managing reality capture data didn’t have to be a struggle?
Why Traditional Storage is Holding You Back
Files Are Scattered Everywhere
Reality capture data is spread across various cloud platforms, internal servers, and external drives. Locating a specific scan means digging through nested folders and searching different systems. Data gets duplicated, outdated, or completely forgotten.
Data Aggregation Is Manual
Combining relevant data together from terabyte-scale datasets is a slow, manual process requiring file-by-file comparisons. Searching by project name, scan date, or asset type is inefficient, and most GIS, BIM, and asset management tools weren’t built to handle the sheer scale of modern capture operations.
Discovery is Slow and Frustrating
Searching for reality capture data feels like navigating a maze; endless folders, mismatched versions, and no clear path to the right dataset. It’s often difficult to even know what the data looks like before opening it. Without proper integrations, reality capture data remains locked in silos, making it hard to use across different tools and workflows. Even well-organized file structures lack intuitive ways to search based on location, time, or metadata.
Reimagining Reality Capture Data Management with LumiDB
The problem isn’t the data—it’s the outdated way we store it. Instead of treating reality capture data like static files, what if it were indexed like a database? This is where LumiDB changes the game.
- Single Source of Truth: LumiDB consolidates reality capture data from scattered locations into a single, reliable source. Everyone, from teams and applications alike, accesses the same up-to-date data, eliminating confusion over multiple versions and lost files.
- Data Aggregation: Traditional file storage makes combining multiple datasets a tedious, manual process. LumiDB removes these barriers by allowing different scans to be merged and analyzed together, while retaining access to the original files in case you ever need to go back.
- API Integrations: LumiDB’s API allows GIS, BIM, and asset management platforms to access structured reality capture data directly.
- Visual Discovery: LumiDB provides an interactive map-based viewer, allowing teams to explore and filter datasets visually. Data can be quickly exported or shared as direct links, reducing file transfers and improving collaboration.
- Flexible Access Control and Lifecycle Management: Unlike traditional file storage, a database model enables granular access control and lifecycle management. Instead of relying on folder-based permissions, data can be structured so that different teams and applications access only the datasets they need. Additionally, LumiDB’s approach allows for tracking, archiving, and phasing out outdated datasets, ensuring that only the most relevant information remains active.
The Future of Reality Capture Data
Clinging to outdated file storage is a costly mistake, draining time, money, and productivity. Poor data management isn’t just an inconvenience; it directly impacts productivity, decision-making, and project costs. Wasted hours searching for files, manually merging datasets, and struggling with outdated tools add up to significant losses. By shifting from arcane file-based storage to modern, easy-to-use visual data management, organizations unlock faster workflows, better collaboration, and long-term data usability. As reality capture data continues to grow, those who invest in better management today will see greater efficiency, and a stronger competitive edge in the future.
Reality capture data is too valuable to be locked in outdated storage. It’s time for a database.
Get Early Access to LumiDB
LumiDB is currently in alpha and available for early adopters!
Written by
