The Young DBA

Hi Friends, This is the 2nd part of my post " Why JSON Came into Picture " .  I am trying to more elaborate how JSON replaces XML and supported in technology upgrade. Background About JSON JSON stands for JavaScript Object Notation, and was first formalized by Douglas Crockford. JSON is a data format interchange - method of storing and transferring data. Mostly its uses such as data conversion (JSON to SQL) and exporting data from proprietary web apps or mobile apps. XML was a big buzzword in the early 2000’s, JSON become the buzzword in later few years. What are the Impacts JSON bring in technology ? NoSQL Document database became popular, mongodb was among one of lucky database vendor.  Technology found JSON as an alternate to xml for data interchange on platform independent. Technology found a supporting for RDBMS to keeping variety of data specially non-structured data in one environment and module. Data explosion and big data came into the platform. Th

What is JSON ? JSON stands for JavaScript Object Notation, and was first formalized by Douglas Crockford. JSON is a data format interchange - method of storing and transferring data. Mostly its uses such as data conversion (JSON to SQL) and exporting data from proprietary web apps or mobile apps. XML was a big buzzword in the early 2000’s, JSON become the buzzword in later few years.  Why JSON came into picture ? After 2005 applications & user requirements started growing rapidly, Hardware and software developed, the advent of Single Page Applications and modern mobile/web apps that we know today needed some kind of data interchange to function seamlessly. To fulfill user requirement technology started shifting into  new language-independent data interchange format that time JSON came into the Picture. JSON gained rapid popularity because it makes transferring data very easy. It’s also lightweight and easy to read and understand. There are few other reasons that JSON make

Last month I got a chance to optimize some queries of a postgre sql database in my current organization. I was totally new to this database. SQL Server, mySQL, MongoDB, and now, postgres. I  never say a 'no' if some work related to database comes to me, and especially, if the database belongs to the RDBMS family, then, I can never say a 'no', as I am always keen to learn new and new trends. My thought for postgres was wrong earlier. I used to think that it is less popular than mySQL, but, I was wrong. When I started working on it, I found it much better mySQL in some scenarios, like - query optimization(using execution plan and statistics). Technically, Postgres is "better SQL" as it is more standardized. With better query planning, so that you can follow the relational model more closely if it suits you. Socially, MySQL has been very popular for a long time and many people are familiar with it. Postgres is neither owned by a major conglomerate with a qu

BLOB/Image/Videos are unstructured data. RDBMS like SQL Server is made to store relational data. File stream is new feature of SQL Server since 2008 to store large data. This is not always the best solution to store images on db. Store the pictures on the file system and picture locations in the database. My previous experience is also saying. Why? Because...

Source : Technet

Dear Friends, We allready know Normalization is the process to optimize the storage and increase the performance of system by eliminating redundancy from database. But there is also circumstances when Normalization can reduce database performance.Due to Joins-Jonis-Joins system makes complex to select a simple record-set. A normalized database requires much more CPU , memory ,  and I/O to process transactions and database queries than does a normalization database. Ref:  1.)  advantages-disadvantages-normalizing-database 2.)  www.informit.com/articles

Enterprise Systems and IT Application can be categories in two types OLTP and OLAP . In General Terms OLTP is day to day Record Keeping of any organization and OLAP is the Historical Data of Warehouse..   OLTP (On-line Transaction Processing)   is characterized by a large number of transactions (INSERT, UPDATE, DELETE). The main emphasis for OLTP systems is put on very fast query processing, maintaining data integrity in multi-access environments and an effectiveness measured by number of transactions per second. In OLTP database there is detailed and current data, and schema used to store transactional databases is the entity model (usually 3NF) OLAP (On-line Analytical Processing)   is characterized by relatively low volume of transactions. Queries are often very complex and involve aggregations(DISTINCT,GROUP BY,SUM,COUNT ..). For OLAP systems a response time is an effectiveness measure. OLAP applications are widely used by Data Mining techniques. In OLAP database ther

Dear Friends , Last week I was doing Database Re-Engineering of our few Legacy Applications. Actually Re-engineering is a set of activities that are carried out to re-structure a Legacy System to a new system with better functionalities and conform to the hardware and software quality constraint. I tested 3 Tools for Data-Modeling for this process. (1) Toad Data Modeler 4.1 (2) Microsoft Visio and (3) SSMS 2008 . Data Modeling is a process used to define and analyze data requirements needed to support the business processes within the scope of corresponding information systems in organizations. All are the good software for Data-modeling but I liked all time favorite SQL Server Management Studio Relationship Diagrams simple-easy, free and having good options.. A little formatting in SSMS database diagrams editor As more tables will be added, these may not be arranged for easy viewing. To change the arrangement of the diagrams you can right click in the

DBMS Database Management System is defined as the software program that is used to manage all the databases that are stored on the network or system hard disk. The database system in which the relationships among different tables are maintained is called Relational Database Management System. Both RDBMS and DBMS are used to store information in physical database. RDBMS solution is required when large amounts of data are to be stored as well as maintained. A relational data model consists of indexes, keys, foreign keys, tables and their relationships with other tables. Relational DBMS enforces the rules even though foreign keys are support by both RDBMS and DBMS.