in real environments • Efficient use of storage space if data normalized properly • Great tools support • ACID semantics • Incredibly flexible and powerful query language • Great framework support
very well with flat tables. • Difficult to evolve Schema with time. • Data constraints and JOINs can be expensive at runtime. • Difficult to scale horizontally.
the way data is being used by individual applications or components of single application. Martin Fowler http://martinfowler.com/articles/nosql-intro.pdf
to find all the jobs. • As a User, I should be able to find all the jobs near to my location. • As a User, I should be able to find all MongoDB (or any skill) jobs near to my location. • As a User, I should be able to find all the MongoDB (or any other skill) jobs near to my location with distance.
Lists, Maps, primitives • Schema-less – Each document is heterogeneous, and may have completely unique structure compared to other documents. • Fast and horizontally scalable • Rich query language
all the MongoDB jobs near me – Find all the MongoDB jobs within London • Supports only two dimensional indexes. • You can only have one geospatial index per collection. • The spatial functionality MongoDB currently has is: – Near – Containment http://www.mongodb.org/display/DOCS/Geospatial+ Indexing
& free-as-in- freedom • You get three free gears, each with 512MB memory and 1GB of disk space. • Need more resources, just ask! • The catch is we are in developer preview right now
can build polyglot persistence applications on it. • MongoDB makes it very easy to build location aware applications. • All the Spring latest projects work without any problem on OpenShift. • Did I mention – Free? • What are you waiting for? Try it out. • Sign up using JUDCON.IN promo code.