Subscribe to RSS feed  Follow @jackvamvas - Twitter

*Use the Comments section for questions Links



Discussing Converged database versus Specialized database engines

05 January,2022 by Rambler

Since I started working with databases there have  been multiple paradigm shifts in management of data.

Some notable changes include

> Moving to different data types , e.g image , video , clob, blob, xml, cursor, table, varbinary, binary , spatial types geometry , spatial geography types

> Number of users & uses  , particuarly through the Internet explosion where the application requirements rapidly multiplied . This new class of applications required storage and search capability for a wider range of entities

> The growth of the Developer community is in parallel to the  rise of special purpose database engines . There is an increasing emphasis on  Rapid development , leading to process changes and flexibility in the way applications are architected and deployed.

Developers require a more efficient method of storing data   either schema or schema-less.   Schema-less data , such as document storage , and mapping the schema to the  application data object , deserves some attention - specifically around  data integrity rules  and where to maintain the rules. Traditionally the advice is to maintain the integrity rules as close to the data as possible - so the rules move with the data.   Now , we're witnessing a distributed model with data across multiple data stores\engines and rules in various phases of the transaction.

Cross-roads in the industry

In general terms , we're at a cross roads in the industry . On the one side , there is the rise of Agile development on such platforms as AWS  - with   package automation around multiple DB engines - available quickly , without the overhead of infrastructure  management  and rapid access to different DBMS engines with layered storage costs. 

On the other side - there are the CTOs and DBAs pushing for a converged database service. This is  noticeable in environments with thousands of databases , supporting a wide range of DIY & vendor applications

The justification for the converged approach is to decrease the fragmentation of data , rationalizing data schemas , challenging the need for separate database engines. The DB engine Vendors are responding by adding new features and data type support with every version upgrade . Most of the large DBMS vendors such as SQL Server, Oracle, PostgreSQL have support for JSON. 

Some other related topics , but contribute to a broader conversation

1) Data Lake -  A data lake is a storage repository holding large amounts of raw data in its native format until it is needed for analytics applications. Hadoop is a good example accompanied with storing data on cheaper storage HDFS .

2) BlockChain technologies fit into these developments. Consider the latest announcements from Microsoft  - SQL Server Ledger Tables and  Blockchain Oracle 






Author: Rambler (


Verify your Comment

Previewing your Comment

This is only a preview. Your comment has not yet been posted.

Your comment could not be posted. Error type:
Your comment has been posted. Post another comment

The letters and numbers you entered did not match the image. Please try again.

As a final step before posting your comment, enter the letters and numbers you see in the image below. This prevents automated programs from posting comments.

Having trouble reading this image? View an alternate.


Post a comment on Discussing Converged database versus Specialized database engines