Customer satisfaction is Ayoka’s focus with our agile delivery for mongodb development services. Ayoka has implemented MongoDB solutions as standalone applications or with integration to traditional relational databases. Examples of custom MongoDB applications include drug interaction applications, pharmacological research and reporting tools, and integration with smart meter (utility) system for energy and water usage analysis and reporting.

One of the problems MongoDB solves in OO (object oriented) programming is impedance mismatch. When describing an entity, the idea of nested object structures has become a typical way of describing things. The way developers model business information in code via objects and the way they are represented in a traditional relational database via tables, has always been troublesome to software developers. Tools such as a object relational mapper are available for most programming languages, but even with these tools the task of performing object-relational mapping is time consuming. MongoDB simplifies this activity and reduces the level of effort to perform it.

  • Domain Model
  • Database Design
  • Performance Evaluation
  • Implementation Services
  • Device Integration
  • Custom Big Data

With the MongoDB document database, the data is stored almost exactly as it is represented by the program and no complex and time consuming mapping is needed. Hence, results are:

  • simplified task of app development
  • eliminates complexity
  • overall faster application development cycle

MongoDB saves data as BSON (Binary JSON, http://bsonspec.org) which provides an efficient serialization format. The total overhead of marshalling is minimal and allows the database to store arbitrary data without the need for a schema. BSON is also designed to be traversed easily and encoding data to BSON and decoding from BSON can be performed very quickly in most languages because of “C” data types hence resulting faster performance.

MongoDB is a popular open source NoSQL Document based database that, properly designed, allows it to enable enterprise applications to perform exceptionally well. It has well regarded features for key / values stores, document databases and RDBMS (Relational Database Management System) relative to other NoSQL databases. It is supported across several platforms such as GNU Linux, Windows, FreeBSD, OSX Solaris. The api (application programming interface) support is provided for programming languages including C#/VB.NET, Java, Python, Ruby etc.

Other features provided by MongoDB are full index support, built in replication, auto-sharding, document-based queries expressed in JSON / JavaScript, Rich queries, Server-side JavaScript, GridFS for storing files of any size, Map/Reduce (for flexible aggregation and data processing, queries run in parallel in all shards), and Geo-spatial indexing.

This technology and NoSQL (Not Only SQL) is a controversial buzzword among database professionals in recent years. NoSQL databases are the minimally structured database with an ability to scale large amounts of data stored across cloud computing applications. The four major technologies under the NoSQL banner are: Key-Value store, Graph Database, Document database and Big Table; together, these allow increased scalability and faster analytics big data applications.

Overall MongoDB’s flexible data structure, ability to index and query data, and auto-sharding makes it an effective tool to adapt changes exceptionally well while reducing complexity to a great extent when compared to traditional RDBMS. Well-designed, MongoDB is flexible, powerful, scalable, and can be added to existing business applications.


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