Running big data on your SQL database instances? Read this blog and deal with big data sets inside your database instances properly.
The performance of databases on bigger data sets is something that’s always of concern to developers. As our data gets bigger, our databases have the increasingly hard task of keeping up with performance requirements. Unfortunately, a dangerous big data scenario can happen.
In this blog, we will walk you through things you should avoid when dealing with big data sets in your database instances.
Here’s a quick set of questions for you before getting into the topic of this guide:
|Is this your first time working with bigger data sets in database instances?
|If you’re a seasoned professional who’s dealing with bigger data sets day in and day out, you will be able to apply some lifehacks to the advice contained in this article. If not, no worries – we’ll walk you through everything you need to know, but it will take some time for you to ramp up.
|How many rows are considered “https://en.wikipedia.org/wiki/Big_data?” How do I know if I’m in the territory of dangerous big data?
|Big data means different things to different people – the number varies depending on who you ask, but we think that anything over 100 million rows is a decent chunk of data that falls under that category. The amount of rows you have will directly impact your decision-making. Dangerous big data territory is the amount of rows that starts to terrify you because you’ve never worked with such an amount in the past.
|What kind of DBMS are you using?
|This is one of the main questions you need an answer to – different database management systems work in different ways and solve different problems, so it’s important to do your research before sticking with any one database management system.
|Do you have experience dealing with databases? Bigger data sets?
|Some of your experience will definitely need to be applied to situations involving big data – in many cases, the simplest solutions work the best.
After you have the answers to these questions, you will be able to move further and explore the landscape of your database. Consider also checking out our guide on how to deal with a database with billions of records.
What DBMS to Choose?
The database management system powering your database is probably the most important thing you have to make a decision. Many experienced DBAs (database administrators) derive answers from their professional experience, but for others, the choice may not be so obvious. Consider this:
After you know this, choose the model most suitable for your specific use case, then proceed into choosing the database management system itself. Be aware that there are loads of data warehousing solutions like AWS Redshift or similar, but the underlying DBMS housing your data is still one of the most important parts for you to decide on.
Configuring the Database
First off, databases must be configured properly. That’s true for any amount of data – database configuration can take us a long way, regardless of whether we’re in a dangerous big data territory or not. Here’s what to do:
These three steps are the main things you need to do in order to make your database avoid big data dangers – of course, you should be aware of your server capabilities when configuring your database too, but it doesn‘t get much more complex than that. Instead, many dangerous big data pitfalls come from situations surrounding your database or data sets. Here’s how to avoid them!
Dangerous Big Data – Pitfalls to Avoid
Some of the most frequent pitfalls in the dangerous big data world are as follows:
These problems are where 80% of big data-related issues come from, and they can manifest in many forms including, but not limited to:
These problems aren‘t new to anyone; however, when bigger data sets are involved, these pitfalls must be properly accounted for to avoid disaster.
How to Avoid Pitfalls?
Here’s to overcome these big data problems:
These tips will be a good base when starting off – however, you must keep in mind that in many cases, advice like that won’t be enough, and you will need to learn from the real world too.
Here are some problems we’ve observed when working with bigger data sets over the years:
And last but not least, also consider SQL clients. Seriously – you have millions (or even billions) of rows in your database instance, and you’re not using one?! Madness.
SQL clients like the one provided by DbVisualizer connect to all the most popular databases. Stop working with your data as if it was a spreadsheet and explore its visual query builder, extensive visualization capabilities, and many other features. Try it today for free!
You’ve read this blog in its entirety, and that means that you should now put your knowledge to the test – make sure you’ve configured your DBMS properly, and don’t fall into any of the dangerous big data pitfalls mentioned in this article. And now that you’re aware of most of the pitfalls you need to avoid when working with bigger data sets, why not read more of our blogs to come up with more solutions to problems? Come back to our blog later on, and until next time.