Five types of databases ideal for Big Data

We’re talking about the ideal database types to handle Big Data. Big Data has emerged as a key IT concept in recent years. This is a term that can be applied to some very specific characteristics related to data scaling and analysis mmc996 Singapore, and it is not necessarily something that can only be used by large companies such as Facebook and Google.

The top five types of NoSQL databases

Five main types of NoSQL databases have emerged: columnar, documentary, graphical, key-value, and XML.

We are going to look at each of these five types of databases, also looking at the type of data analysis that best fits each of them.

Columnar databases

These are the most similar NoSQL databases to conventional relational databases. They store structured data in individual columns (instead of tables).

These databases use groups of columns. They work well for machine-generated data, structured data sources too large to be handled by a single computer, and for quick data queries.

If you are thinking of fast and accurate data-machine analysis, these may be the ideal database types. Apache Cassandra and Apache HBase are some of them.

Documentary databases

These types of databases are based on document storage rather than structured data.

They are good for unstructured data, such as open text from a letter or email, and semi-structured data such as academic documents.

You will have to pay attention to them if you are thinking about text analysis of documents too big for conventional databases. Some of the best known are MongoDB and Apache Couch DB.

Graphical databases

These types of databases use a graphical structure that is essentially a diagram of the relationships within the data, rather than tables.

They are good database engines for driving web applications that must provide information very quickly, such as those used for online shopping and social media platforms.

You will need to look at these types of databases if your main interest is a quick application, and you can live with some analysis approaches. Some of the best known are Neo4J from Neo Technologies and Microsoft Horton.


These are designed for simple and easy application development.

They are good for situations where you need to work with rapidly developing applications and where all other considerations are secondary. Some of the best known are Basho Technologies’ Riak and Redis.


These types of databases use the XML language, which is the underlying language of the Web and many other information exchange systems, to define the data structure.

They are good for data management that cannot be obtained with any other type of database, and a good match when you have a large amount of data in non-traditional formats, such as video and audio.

You’ll need to look at these types of databases when you need to dig deeper into unstructured data analytics like voice or video analytics. Some big names in these types of databases are Mark Logic and Sedna.

Author: Evelyn Obrien