We’ve been speaking about MongoDB at physical events like conferences and meetups. But since there’s interest in MongoDB from many different geographical locations, we thought we’d also do a webinar. This will be an interactive live web event. Look forward to seeing you there!
If you have questions on the webinar or have ideas for other such webinars shoot us an email at firstname.lastname@example.org.
Software developers often debate the pros and cons of static versus dynamic typing in programming languages. Yet what about databases?
Of course, static typing is traditional for databases. In a relational database we usual declare our columns and the datatype of each column’s values.
However, we now see in the nosql space what are known as “schemaless” databases. Technically these products are often have some schema: for example in MongoDB we define collections and indexes. However, we do not predefine the structure of objects within those collections — they may all be different, or all the same. The typing is dynamic.
Dynamically typed databases are a good fit with dynamically typed programming languages.
It certainly feels like it would be a win to have a dynamically typed db when using a dynamically typed programming language (Ruby, PHP, Python, Erlang, …) How suboptimal it would be to have all the flexibility of dynamic typing in our code, and then hit a “brick wall” when we go to persist the data and have to statically spec everything out! There is synergy to be had between the dynamically typed programming language and the dynamically typed database.
Dynamically typed databases can be a good thing when using statically typed programming languages.
The best thing about static typing with compilers is that errors are reported at compile/development time. This is a big win for statically typed languages such as Java and C++. However, even with a statically typed database, type matching errors storing data are only reported at runtime! (That is, our java compiler doesn’t check our MySQL schema.)
Thus some of the power of static typing in programming is lost at the storage layer. We still retain some benefits: assurance of some consistency to the data stored. But any failure to honor such a contract is only reported at runtime. Thus, it is more than worth considering using a “schemaless” database with say, Java, and getting out of the business of writing data migration scripts with each release. (Yes, some of that work stays but we can eliminate the majority.)
Relational databases could be dynamically typed.
While existing RDBMSes are statically typed, this is not an inherent limitation of the relational model. One could imagine a relational database with tables where one can dynamically insert a row with an extra column value at any time, and where values of cells in the same column of a table may have different types.