SpaceCurve – New Dimensions for Big Data

In December 2014, SpaceCurve will announce a spatial data platform that is designed for big data systems and spatial data, enabling real-time ingest, index, query and correlation of spatial, sensor, “Internet of things”, mobile device, social media and other streaming and historical data sources for real-time analytics and business insights. SpaceCurve has completed beta testing, the solution is generally available and they have five customers.

Traditional data architectures weren’t designed to handle spatial data at the speed and scale required to gain insight that can answer complex spatial questions in real-time. SpaceCurve has been architected for large volume (imagery data, for example) fast-moving data (from sensors) and the complex fusion of several types of data (weather, chemical, terrain, for example.)

Background

Conventional databases are designed to manage various numeric and character types of data found in text and documents, while a spatial database is optimized to store and query spatial data or data that defines a geometric space. In a spatial database, data is stored as coordinates, points, lines, polygons and topology, and in some cases more complex data such as 3-D objects, topological data and linear networks.

Because of this, existing databases have limitations that can impact their effectiveness in storing and analyzing today’s “Big Data”. These platforms aren’t optimized to handle streaming sensor data with spatial and time series attributes, and they are unable to provide the scale and performance that allows this type of data to be analyzed in real-time for immediate action. According to Bloomberg News, by the year 2019, there will be 2.8 trillion sensor devices worldwide up from 65 million today. This growth in sensor data, coupled with similar growth trends in social media and mobile device data will strain conventional database infrastructure.

Products exist on the market including Open Source solutions for Big Data (like Hadoop) and GIS Mapping solutions (like ESRI), SAP HANA, and BigTable, a highly scalable distributed storage system that is used in Google Maps – but none of these solutions scale to the requirements of data with space and time attributes or have been designed to enable real-time decision- making using this data.

SpaceCurve

SpaceCurve had its origins in 2006, at which time founder Andrew Rogers characterized the problem with traditional systems as being related to four computer science problems that needed to be solved in order to provide the right spatial technology. The solution had to provide a living model of the world, indexing everything, including the internet, social and sensor data, such that the model would be continuously updated to provide real-time analysis of the “patterns of life”.

SpaceCurve received its first round of funding in 2010 and has secured a total of $16.3M from 4 investors including Reed Elsevier Ventures, Musea Ventures, Divergent ventures and Triage Ventures. Latest funding was $5M on March 5, 2014.

SpaceCurve is an active member of the Open Geospatial Consortium (OGC), an international industry standards organization with 497 companies, government agencies and universities working together to develop “publicly available interface standards that will enable interoperable solutions that “geo-enable” the Web, wireless and location-based services and mainstream IT. The standards empower technology developers to make complex spatial information and services accessible and useful with all kinds of applications.”

The Technology – A Closer Look

SpaceCurve has architected a new high-performance database from the ground up that is specifically designed to handle real-time sensor data as well as data from other sources, continuously indexing and storing this data to enable spatial interactive analytic queries that can’t be done by Oracle Spatial, PostGIS, BigTable or Hadoop. New algorithms and data structures support massive distribution of geospatial and sensor data models and parallelization of spatial operations. Spatial context connects data and brings a spatial context to data-driven decisions by using a live real-time distributed index that preserves spatial proximity across all data sources The computational geometry engine provides high-precision space and time analysis optimized for geospatial applications that cannot tolerate even a 1% error rate ( typical in other solutions).

SpaceCurve believes that there are three characteristics that make their database unique: (1) High Velocity Data Ingestion (2) Real-time Query Execution and (3) Spatial Relationship Analysis

Key features and benefits:

  • Unified spatial data model — all data in one place
  • Supports common spatial data formats
  • Subsecond latency from data insertion to analysis
  • Scalable on clusters of commodity servers
  • Native support for interoperability standards such as REST/JSON and OGC
  • ESRI and Hadoop integration out of the box
  • Support for points, vectors, polygons, and raster data.
  • Exceptional spatial calculation precision and performance suitable for the most demanding spatial analysis
  • Uses SQL-based query interface to reduce learning curve
  • Cloud-based, elastic computing model
  • supports scale -out

And what kinds of things can be done with a spatial database that can’t be done with a traditional solution? This type of spatial data platform can answer questions like “What are the optimal aircraft settings for my aircraft in this weather?” Airplanes are equipped with a wide variety of sensors that provide real-time streaming information on many factors including temperature, pressure, and humidity which can be collected and correlated to assess their impact on various plane systems. By looking at historical data from sensors, an optimized flight set-up can be determined. By combining that with data collected in real-time, the data can be understood within the current context and adjusted based on real-time conditions, adapting the flight characteristics/aircraft settings based on contextual changes (weather, airport conditions etc.).

SpaceCurve Go-to-Market

SpaceCurve is targeting several industries that can benefit from this technology including:

  1. Telecommunications –managing huge networks looking at network sensor data in real-time, detecting patterns of human migration as well as movement in real-time to understand the density of people in a given location at a particular time.
  2. Transportation and Logistics – delivering people and products from one location to another by detecting the best/fastest/most economical route possible.
  3. Military Operations – evaluating sensor data collected by drones for military intelligence.
  4. Others including state & local government, oil/gas extraction, precision agriculture and crop management.

SpaceCurve can be purchased in an on-premise licensed software model or as a software-as-a-service (SaaS) offering to operate in the Amazon Web Services cloud.

 Summary Observations

SpaceCurve looks to be “in the right place at the right time”. Of Gartner’s top ten technology trends for 2014, SpaceCurve’s spatial big data platform incorporates 5 of them including: web-scale IT, smart machines, the Internet of Everything”, IT as a service broker and cloud/client architecture. In this new world, spatially aware sensors in the “Internet of Things” will talk to each other, machine to machine and make context-based decisions in real-time.

With huge growth predictions for big data, particularly in sensor, mobile, and social data, current database technology just can’t handle the scale, volume and new data types. SpaceCurve’s purpose-built platform is designed specifically to address the limitations of traditional databases. Beyond that, built-in analytics are capable of gleaning new insight from this data in real-time.

SpaceCurve seems to be a natural fit for their target industries (Telco, Transportation, Defense) and I suspect that over time, new applications in a wide range of industries will present themselves. SpaceCurve’s challenge will be to use this foundation of early wins to leverage additional opportunities in these markets and in adjacent industries. With ground-breaking technology, a recent round of funding, and thought-leaders in key positions, SpaceCurve is poised to dominate the emerging market for spatial database technology.

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