Intro To Database Systems Week 7

 A major difference between MongoDB and MySQL is that MongoDB is a non-relational database while MySQL is a relational database. This means that in MySQL, data is stored in table columns and rows that have a particular schema. However in MongoDB, a non-relational database, data isn't stored in columns and rows with a particular schema. Instead data is stored in a less structured form where various database styles can be implemented such as a key-value, wide column, document, and graph databases. A similarity however is that both relational and non-relational databases seem to have keys for their rows or documents. When deciding when to choose between the two styles, I would most likely choose a relational style when I need a strict schema and higher efficiency. Though I would choose a non-relational style when different data points may be needed in different documents, providing a more dynamic model.

Comments

Post a Comment

Popular posts from this blog

Software Engineering Week 4

    The most interesting thing I have learned about in my reading of "Software Engineering at Google" are how each of the various processes are executed. While I am familiar with most of the processes I've read about so far, including code reviews, unit testing and system testing, the manners in which these are executed at Google are different from how they have been executed in my professional experience. For code reviews in particular, Google engineers ensure they invite various other software engineers to fill the roles of correctness and comprehension checking, language readability checking, and code owner. However, in my experiences this is not explicitly required. While a single engineer on the team often fills a couple of these roles, there wasn't an engineer specifically dedicated to carry out each of these tasks. Another interesting thing I learned was a recommendation about the use of the "sleep()" function in testing. While sometimes waiting is re...
Read more

Capstone Project Week 10

   What did you accomplish this week? This week I looked into integrating the stac-browser container within the docker compose YAML file provided in the stac-fastapi-pgstac project. In addition I cleaned up some unnecessary data included in STAC items written by our parser as well as read further documentation from the National Hurricane Center on how I can do additional parsing on dropsonde remark messages. I also published a build and tested docker image including our team's parsing tools to docker hub to allow it to be pulled from our AWS instance. What is your plan for next week? Next week I will work with my team to get our STAC Server running and hosted within an AWS server for demonstration and testing with our stakeholders.  What challenges, if any, are you currently facing in project development? Do you need instructor assistance?  So far local development has been smooth on a Windows 11 operating system. Containers are able to be built and ran using docker...
Read more

Capstone Project Week 11

What did you accomplish this week? This week I pushed updates to our parser development branch which included additional parsing for remarks and removal of certain metadata properties that were unnecessary for describing the who, what, when, and where of a dropsonde message. In addition I was able to get our parser, STAC API, and STAC browser containers running and hosted AWS, load our STAC database with STAC items using our custom API endpoint integrated with our parser, and test our application's availability on the internet. After confirming our application's accessibility, I scheduled a demonstration with our mentor to show our progress and attain feedback. What is your plan for next week? Next week I will demonstrate our STAC parsing and catalog browsing capabilities within our container hosted on AWS to our project mentor.   What challenges, if any, are you currently facing in project development? Do you need instructor assistance?  I'm not facing any challenges at...
Read more