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It may be a bit off-topic. I am eager to know the industry specific importance of Spatial Databases.

Is Spatial Database a very important part of any GIS system? Or will we use other technologies to store and retrieve spatial data in the near future?

I want to know these things because soon I am going to persue MS on Spatial Database Optimization.

Thanks

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By "Spatial Database" are you accepting the definition provided by Wikipedia at en.wikipedia.org/wiki/Spatial_database? If you are defining it as identical to a Spatial DBMS then the responses may be different. For example, I would say that a File Geodatabase is a Spatial Database but not a Spatial DBMS, and is often used for GIS at the Project and Department level. – PolyGeo Jul 4 '11 at 23:45
No I am talking about Spatial Database one which is mentioned at Wiki(i.e SDBMS) – MiNdFrEaK Jul 6 '11 at 11:54
I'm not able to find it, but I think a similar question was posted already. Do someone remember about that? – simo Jul 7 '11 at 12:41
Lately I've been asked about SOLAP but haven't found much discussion about it. I think this would be a good research area. – Kirk Kuykendall Jul 7 '11 at 14:31
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It is not a particularly great discussion of SOLAP, and somewhat outdated but my thesis dealt with SOLAP in the context of the Arc Marine Data Model dusk.geo.orst.edu/djl/theses/brett/brett_thesis.pdf. or the "Transactions in GIS" version of it onlinelibrary.wiley.com/doi/10.1111/j.1467-9671.2009.01159.x/… – blord-castillo Jul 7 '11 at 15:56

3 Answers

up vote 3 down vote accepted

Spatial databases provides services to store and manipulate geometries, generally positioned in a geodetic system. The importance of the spacial database behind your GIS will mostly depend on the usage, but generally speaking, you can hardly talk of GIS if you don't have a proper spatial database for data storage.

Due to the fact that computers can only manipulate linear, one dimension data, you can split spatial databases in two logical parts :

  • Geometry manipulation and indexing, with geodesy support
  • Storage technology

The algorithms and logic used for the geometry manipulation are really specific, and then mapped to "classical" one dimension data to make them directly compatible with computers for storage. The only feature that have one foot in each world are the spatial-aware indexes, that uses algorithms similar to R-Trees.

For the storage, any underlying technology can fit, and won't change much the way you manipulate the spatial data. It might be a SQL database (and assimilated technology) or some kind of noSQL storage or something else. The main thing that will change is the spatial indexing, any other feature can be implemented with no major drawback (well except the occasional additional work).

So here is my conclusion : if you learn the way how to manipulate spatial data efficiently, and, depending on your ability to learn new technologies, you will be able to adapt whatever the technology is actually used. Learning the general concepts behind spatial data, especially for relational manipulation, is the hard part, and uses mature concepts that are not likely to change.

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I don't have as thorough an answer as Valise, but I think that there is future in using Graph (NoSQL) databases for the storage and retrieval of spatial data. The graph structure is used already quite extensively in GIS data (think of nodes and arcs). There are some efforts already but I haven't used them. See Neo4j spatial for example: http://wiki.neo4j.org/content/Neo4j_Spatial . Graphs also can be used to store the indexes mentioned above...

Just my two cents...

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Spatial Database Management Systems are very important in GIS (just look at this site for proof). An emphasis has always been placed on spatial databases that are based on the relational model. However, there are numerous examples of different data models, and processing approaches that can be used:

  • Raster data uses structures based on matrices.
  • Spatial indexes make use of tree data structures.
  • Network analysis use data structures and algorithms related to graph theory.

All these approaches have a place in GIS, and have advatages and disadvantages. From the perspective of the GIS user, a Spatial Database is an abstraction that hides a particular data structure and set of algorithms. You do not need to know the intricacies of predicate logic to do a bounding box query.

Personally I see the future of spatial databases as divergent. We are hiding more of the underlying technology and making it easier for users to ask GIS questions, and make maps. Good examples are SimpleGeo, Google Maps APIs, and Fusion Tables. On the other hand we are pulling in code from other domains such as using R for raster analysis, and using graph databases as dslamb mentioned.

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