Although NoSQL databases are relatively new, they've quickly adopted geo, from basic bounding box queries to full geospatial indexing, query and projection on a par with PostGIS. This presentation introduces NoSQL to the Geo developer, describing the pros and cons of NoSQL vs. relational, and what Geo functionality exists in the leading products.

1. The NoSQL Geo Landscape
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2. Why NoSQL?
• Cost
• Scalability
• Developer-friendly
• Web-friendly
 HTTP
 Javascript/JSON
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3. Where did NoSQL come from?
IBM
1970-2000:
Mainly
RDBMS
solutions
2000-2005:
DotCom bubble,
new scale, NoSQL
beginnings, white
papers
2005-2010:
Open source
and Mainstream
2010+:
Adoption of
cloud  DBaaS
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4. What is NoSQL really?
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NoSQL  “Not only SQL”  Non-Relational
New ways of querying, defining, and
designing your dynamic data store…
for a different breed of scale problems…
Scale = data size and concurrent users
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5. What ties NoSQL databases together
• Many varieties!
 Key-Value
 Document
 BigTable/Column-Oriented
 Graph
• Some commonalities (usually)
 open source roots
 global database key: easier to partition or shard the data
 more use-case-specific and developer-friendly than RDBMS
 flexible schemas
 favor availability and partition tolerance over consistency: CAP
theorem
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6. IBM
Consistency • Availability • Partition Tolerance
CAP Theorem
When you’re doing something a million times a second,
a one-in-a-million failure happens every second
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7. This is not GIS!
• Very little
• Spatial analysis
• No
• Spatial operations
• Raster data
• Raster (Map) algebra
• Mapmaking
• We’re talking high-performance storage and retrieval!
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8. Polyglot persistence
• Polyglot: “someone who speaks or writes several languages”
• Polyglot persistence: solve a complex data layer problem by breaking
problem into segments and applying different database models
• Common in the industry
• Relational and NoSQL for specific use cases
• Use Apache Solr search on top of MySQL database
• Cloudant (and others) use Lucene search libraries
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9. The survey…
Name Index strategy Data types Query types
Amazon
DynamoDB
IBM
geohash point BBOX, radius
GeoCouch
(CouchDB/Couchbase
)
R-tree point/line/poly BBOX, radius
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Cloudant
R*-tree GeoJSON types BBOX, radius,
arbitrary shape
Lucene/Solr geohash point
(JTS adds more)
BBOX, radius
(JTS adds
polygon)
Orchestrate.io geohash point BBOX, radius
Microsoft
DocumentDB
- - -
MongoDB geohash/quadtree GeoJSON types BBOX, radius,
arbitrary shape
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10. Recommended reading
• Google’s MapReduce white paper
• Data processing on large clusters
• Amazon’s Dynamo white paper
• Clustering for high availability for distributed databases
• NoSQL Distilled
• Architecture and concepts of NoSQL
• Seven Databases in Seven Weeks
• Data Access for Highly-Scalable Solutions: Using SQL, NoSQL, and
Polyglot Persistence
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11. Thanks
IBM
Questions?
Raj Singh
IBM Cloudant Developer Advocate
rrsingh@us.ibm.com
@rajrsingh
http://www.linkedin.com/in/rajrsingh
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