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Is the Relational Database Doomed?
DB Guy writes "There's an article over on Read Write Web about what the future of relational databases looks like when faced with new challenges to its dominance from key/value stores, such as SimpleDB, CouchDB, Project Voldemort and BigTable. The conclusion suggests that relational databases and key value stores aren't really mutually exclusive and instead are different tools for different requirements."
Especially when the claim is as ridiculous as this one.
There's a reason relational databases took over the world of databases: They provide a good combination of flexibility and structure to efficiently represent data. Which is what databases are supposed to do.
I am officially gone from
Leave us RDBMS dinosaurs alone. String Name/Value pairs, that is a great innovation. In other news, Sun will be dropping all types from the Java object system and rely on the VOID type. Idiots.
In headlines, "?" implies that something is a serious question, whose answer is likely to be yes. One that makes it worth spending the time to read the article.
Imagine the headline said "Does Obama Smoke Crack?" and the article had a bunch of stuff about the president, with a last paragraph saying: "There is absolutely no reason to thing that President Obama has ever smoked crack."
-- Support a free market in the field of government
There's a reason relational databases took over the world of databases: They provide a good combination of flexibility and structure to efficiently represent data.
Especially since so many databases really are inherently relational. The textbook example of 1-customer:n-invoices, 1-invoice:n-items plays out quite a bit in the workplace.
Dewey, what part of this looks like authorities should be involved?
no, the relational database is not going anywhere, you are correct. but, that does not mean that there aren't instances where a non-relational database, with the addition of map/reduce, aren't extremely useful.
non-relational databases have been around for decades, and are in use for quite a number of applications involving rapid development and storage of very large records. couple this with map/reduce, and you have the ability to scale quickly with very large datasets.
scaling quickly is a very difficult problem to solve with an RDBMS - you either need to continue to throw more hardware at the problem, to the point of diminishing returns, or re-architect your data at the cost of possible significant downtime, while still attempting to serve up the data in a timely manner. i've been deep in the bowels of oracle RAC, fighting to get just 5% more speed out of a query over a billion rows and realizing that i have to start over with a new schema, just to squeeze more data out. compare that to simply adding another machine and letting the map functionality run across one more cpu before returning it for the reduce.
once again, correct, but having to denormalize to a snowflake or a star isn't always the best solution. you're taking the best parts of the relational database model, and throwing them out - normalization, referential integrity, just to squeeze more out of something that may not be the best tool for the job.
do you hammer with a wrench? i have before, and i managed to hurt my thumb.