I think the ultimate question is: Can all the benefits of a traditional relational data warehouse be implemented inside of a Hadoop data lake with interactive querying via Hive LLAP or Spark SQL, or should I use both a data lake and a relational data warehouse in my big data solution? The short answer is you should use both. The rest of this post will dig into the reasons why.
The love affair with the noSQL (BigData) databases seems to be over. Many of the projects using Hadoop and the other “not” relational databases have fallen by the wayside. Some things like structured data are still done better on the old school relational database server s and accessed with SQL or some SQL tool. As the amount of unstructured data increases so will the use of noSQL databases.
Via: Is the traditional data warehouse dead?
Debugging – the process of finding and fixing defects in software – can be a challenging task to do in all languages. Node.js is no exception. Luckily, the tooling for finding these issues improved a lot in the past period. Let’s take a look at what options you have to find and fix bugs in…
I am at the level with Node.JS that I no longer “Suck at it” but I am still learning every time I use it. One of the areas I struggled with was debugging, which was much different and difficult than my .NET and PHP days. It seems like open source meant that you were on your own for debugging.
Special thanks to Gergely for his article on just the topic of Node.js debugging.
One of the takeaways in the article is Pino is an extremely fast Node.js logger, inspired by bunyan. In many cases, pino is over 6x faster than alternatives like bunyan or winston
I had tried Winston as it was recommended by one of my programmer gods. I was not worthy because I couldn’t understand it. I have high hopes for Pino.
via How to Debug Node.js with the Best Tools Available — RisingStack Engineering
Back in the days time four, I was a hierarchal database specialist. Anyone remember hierarchal, flat files or indexed sequential access (ISAM)? When relational DBMS took off, back in days times two, I became a relational convert and preached the benefits of SQL in all of it’s English like glory. Then I suffered through DDL hell and mapping madness, but I stayed true to the cause. Well, now I’m a Not Only SQL (NoSQL) first level apprentice and speak the Mongo and Hadoop chapters of the Database bible. What’s worse is that I’m a flip-flopper between the relational and document worlds. What I’ve learned is you don’t have to pick the Right side or the Left side, you will end up eating both sides eventually.
Take some time to learn the NoSQL side of the database house. Install Mongo on your system, get a few sample NoSQL databases, use the Mongo command line just to learn some of the syntax. There are a ton of YouTube videos and Udemy courses on this stuff. Once you’ve created your first table (Document) without the Create Table… you might like it. Mikey did, he likes everything.
This article from Lisa Vass is a good introduction as to why and when you should choose. It’s not surprising that relational databases are not doing as much of the lifting as they have in the past.