The NoSQL Geospatial Landscape

Dec 8, 2014Download as PPTX, PDF10 likes7,308 views

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.

The NoSQL Geo Landscape
© Copyright IBM Corporation 2014

Why NoSQL?
• Cost
• Scalability
• Developer-friendly
• Web-friendly
 HTTP
 Javascript/JSON
IBM
© Copyright IBM Corporation 2014

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
© Copyright IBM Corporation 2014

What is NoSQL really?
IBM
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
© Copyright IBM Corporation 2014

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
IBM
© Copyright IBM Corporation 2014

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
© Copyright IBM Corporation 2014

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!
IBM
© Copyright IBM Corporation 2014

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
IBM
© Copyright IBM Corporation 2014

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
IBM
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
© Copyright IBM Corporation 2014

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
IBM
© Copyright IBM Corporation 2014

Thanks
IBM
Questions?
Raj Singh
IBM Cloudant Developer Advocate
rrsingh@us.ibm.com
@rajrsingh
http://www.linkedin.com/in/rajrsingh
© Copyright IBM Corporation 2014

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The NoSQL Geospatial Landscape

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 © Copyright IBM Corporation 2014

4. What is NoSQL really? IBM 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 © Copyright IBM Corporation 2014

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 IBM © Copyright IBM Corporation 2014

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 © Copyright IBM Corporation 2014

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! IBM © Copyright IBM Corporation 2014

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 IBM © Copyright IBM Corporation 2014

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 IBM 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 © Copyright IBM Corporation 2014

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 IBM © Copyright IBM Corporation 2014