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“While performance is often the determining factor, it is necessary to consider aspects such as functionality, ease of operation, availability of professionals, safety, tools and a community that supports the product” Vicente Ayestarán NoSQL Manager at Paradigma

During the last decade we have seen the birth of a new type of database, known as NoSQL.

The rise of the Internet as an application platform has tested the domain of relational solutions. The volume of data that a Web application must face has grown exponentially in recent years, as have the number of users who use them. In addition, these users now demand an immediate response.

At Paradigma more and more often we are implementing NoSQL solutions, thanks to benefits such as improved productivity of development teams, and the ability to get to market faster and with greatly reduced TCO.

The NoSQL technologies have evolved to address different problems, and although they have much in common, they are also very different.

No SQL case studies

We work with all NoSQL databases

Type Key / Value
They have the simplest model of all data associated with a key indexed value.

They are designed to scale massively maintaining a fast response time and overall availability. They are commonly used to store session information, user preferences or profiles, shopping carts and generally as caches of any set of information that can be recovered by a key. Examples are Redis, Riak or Aerospike.

The standard document used mostly in JSON format to store and retrieve information.

They allow you to manage information with complex hierarchical structures and provide full secondary indexes and query languages ​​and data aggregation. This, coupled with the flexibility of the data schema become the most versatile, general-purpose. Within this group we have technologies such as MongoDB, CouchDB or couchbase among others.

The data model focuses on entities and the relationships between these. Both entities (nodes of degree) and relationships (edges) may also have attributes. An entity may have numerous relationships with any other entity. Browse connections between entities through these relationships is the strength of the database oriented graphs, and they allow you to do it with great speed, regardless of the volume of data, allowing you to explore connections between entities which otherwise would be very difficult to with a relational database.

The best known case of this type of database use are social networks.
Examples of this technology are Neo4j, OrientDB or Titan.

Such databases are similar to a table in the relational database, and are in fact derived mostly from the BigTable model published by Google, but a record can contain any number of columns (or column families).

They are ideal for queries and aggregations over large amounts of data when they can be determined in advance and do not change frequently. In this group we find examples like Cassandra and HBase.


NoSQL is Not Only SQL

Choose an agnostic vendor and unite the best of both worlds.

These databases do not have to be the only piece in the storage solution, but will often be accompanied by SQL databases, which still have a safe future, and even other NoSQL databases, a situation that has been baptized as “Polyglot Persistence”.

At Paradigma we are experts in micro service-based architectures, where more and more we will see how each service encapsulates its own data management solution, using in most cases several of the NoSQL technologies available.

MongoDB Advanced Partner

MongoDB’s hugely popular database with a large developer community due to its simplicity and scalability, combined with Paradigma’s solid reputation as one of the top software services consultancy providers have now combined their strengths to service large corporate customers who are investing in innovative and efficient solutions. Visit our blog for more information. If you are looking for a NoSQL solution like MongoDB for your company, contact us.