Some helpful resources:
Lara Gurol, Berk Akipek, Hala Alkhellow
https://docs.google.com/document/d/1sdoUBWRLFesH82a_R55rwWeqc6sa3X62YD4P2_ZUj-g/edit
1. What is the difference between SQL and NoSQL?
2. What is referencing and what is embedding in MongoDB?
Referencing means that the documents in a collection will be held separately. Therefore, the child document is going to have a reference to the parent document.
In embedding, parent document includes child documents in a nested manner. There will be no need to give a reference to the parent document.
3. Why should we embed more than referencing when we can in MongoDB?
Embedding is faster than referencing because we can read and update data in a single operation up to 16 mb. It is easier to use.
Generally used for one-to-many relations. "Has a", "contains" relation.
4. When should we prefer referencing over nesting in MongoDB?
If we have large files, a lot of child documents and we need fine control, we might use referencing. Referencing is also advantageous when we have many-to-many relationships.
5. What are ORMs? Why we use them? Give an example of an SQL request with and without using ORM.
ORMs -Object Relational Mappings- are simply libraries that make it easier to communicate with the databases. Normally, we are supposed to write full SQL queries as strings to communicate with the database. However, these SQL queries are time consuming and error-prone; even one typo would make our query fail. At that point, ORMs come to the rescue. Instead of typing queries by hand as a string, we use the commands of related language which behind the scenes uses SQL to communicate with the database.
6. What is the difference between a table and a collection?
Tables are used in SQL. Each row in a table has the same number of columns.
Collections are used in NoSQL. They are similar to the tables in SQL; however, each document in a collection can have a different number of columns.
Huzeyfe Abdullahoglu, Emine Cig, Sara Hamoud, Adnan Khaldar
1.What is the difference between SQL and NoSQL?
SQL databases are table-based, while NoSQL databases are document, key-value, graph, or wide-column stores. Some examples of SQL databases include MySQL, Oracle, PostgreSQL, and Microsoft SQL Server. NoSQL database examples include MongoDB, BigTable, Redis, RavenDB Cassandra, HBase, Neo4j, and CouchDB.
SQL databases are relational, NoSQL databases are non-relational.
SQL databases use structured query language and have a predefined schema. NoSQL databases have dynamic schemas for unstructured data.
SQL databases are vertically scalable, while NoSQL databases are horizontally scalable.
SQL databases are table-based, while NoSQL databases are document, key-value, graph, or wide-column stores.
SQL databases are better for multi-row transactions, while NoSQL is better for unstructured data like documents or JSON
Embedding can be explained by the idea that one embeds data inside each other.
Referencing can be explained by one arranging 2 or more data sets separately, but connect them with key data that is called a “reference.” Thus, they could be separate yet connected.
3.Why should we embed more than referencing when we can in MongoDB?
it’s faster than referencing, we can read and update data in a single operation
4.When should we prefer referencing over nesting in MongoDB?
We can think of an example: having a biiig box that has everything about our computer. Finding a battery for our mouse inside that big box would be like hell! But when we have smaller boxes, all labeled “computer components,” and some other info, we could easily find everything we need, in seconds.
5.What are ORMs? Why we use them? Give an example of an SQL request with and without
using ORM.
ORMs -Object Relational Mappings- are simply libraries that make it easier to communicate with the databases.
6.What is the difference between a table and a collection?
Instead of tables, a MongoDB database stores its data in collections. A collection holds one or more BSON documents. Documents are analogous to records or rows in a relational database table. Each document has one or more fields; fields are similar to the columns in a relational database table