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The NoSQL Geospatial Landscape

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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.

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The NoSQL Geospatial Landscape

  1. 1. The NoSQL Geo Landscape © Copyright IBM Corporation 2014
  2. 2. Why NoSQL? • Cost • Scalability • Developer-friendly • Web-friendly  HTTP  Javascript/JSON IBM © Copyright IBM Corporation 2014
  3. 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. 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. 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. 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. 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. 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. 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. 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
  11. 11. 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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