When defining what a cloud service is, we need to know that it is not a technology per se, but its an architectural and operational paradigm. It is a self-service computing environment offering the ability to create, consume, and pay for services. In this architecture, computing resources are elastically supplied from a shared pool and charged based on metered use and it uses service catalogs to provide a menu of options and service levels.
Perhaps you’ve come across a great cache of publicly available SQL scripts that would be very useful in monitoring your databases, and these scripts are hosted on github. Getting those scripts is as simple as clicking the Download button.
What if, however, you wish to contribute to the script library?
Or perhaps you would like to collaborate with coworkers on a project and want to host the files on github.
How do you get the files to your local server so that changes can be saved and pushed to the master repo?
Roughly speaking, the notion of ‘Tables’ in Oracle is similar to MongoDB’s ‘Collections’. They are NOT identical though. Before we examine the differences between Oracle’s Table and MongoDB’s Collection, let’s see what Table in Oracle and Collection in MongoDB are.
Table in Oracle:
A table in Oracle is made up of a fixed number of columns for any number of rows. Every row in a table has the same columns.
Collection in MongoDB:
This Log Buffer Edition covers the top blog posts of the week from the Oracle, SQL Server and MySQL arenas.
One of the main MongoDB DBA’s task is to monitor the usage of MongoDB system and it’s load distribution. This could be needed for proactive monitoring, troubleshooting during performance degradation, root cause analysis, or capacity planning.
Mongostat is a nifty tool which comes out of the box with MongoDB which provides wealth of information in a nicely and familiar formatted way. If you have used vmstat, iostat etc on Linux; Mongostat should seem very familiar.
Sun of database technologies is shining through the cloud technology. Oracle, SQL Server, MySQL and various other databases are bringing forth some nifty offerings and this Log Buffer Edition covers some of them.
Partitioning a large table is general practice for a few reasons:
This Log Buffer Edition throws spotlight on some of the salient blog posts from Oracle, SQL Server and MySQL.
Nowadays Cassandra is getting a lot of attention, and we’re seeing more and more examples of companies moving to Cassandra. Why is this happening? Why are companies with solid IT structures and internal knowledge shifting, not only to a different paradigm (Read: NoSQL vs SQL), but also to completely different software? Companies don’t simply move to Cassandra because they feel like it. A drive or need must exist.