Pretty interesting graph extracted from Presentation: Scale at Facebook

Relative Performance of Language Runtime

I knew PHP has pretty huge performance overhead but boy, just look at Ruby and even Python!

But I am not so sure that Python’s performance cost is as equal to PHP because Python has the ability to generate compiled files also which certainly boost performance.

Recently there has been lots of talk about using hybrid databases for a system like: using traditional SQL based database for storing static data and using Key-Value stores (Cassandra, HBase) and document based databases (MongoDB, CouchDB) for storing data domain with high magnitude of frequency of changes.

This approach seems more pragmatic as compared to using a single database implementation. And once again, one should not forget that one solution does not fit every contexts.

Presentation from Pycon:

The presenter is telling that Redis is the only of its kind in NoSQL ecosystem which is not true because MongoDB is also in-memory database but unlike Redis its document based while Redis is more key-value values based.

Apart from that, the talk is worth watching!!!

It’s been quite sometime I’ve been subscribing to Planet CouchDB and it’s a great resource for getting new information about NoSQL technologies especially CouchDB.

From the same source, I got chance to read these two interesting blog posts. One was about criticizing Amazon SimpleDB and overall NoSQL technologies and other one being answer to that criticism.

One can find large number of articles and blog posts arguing SQL and NoSQL group. It seems like whole database world has been divided into two camps just like during Cold War: capitalism and socialism (I won’t select which one is capitalism and communism, decide yourself ).

In my opinion, all these arguments and counter arguments are kind of unnecessary because both of these tools are quite powerful in their respective context.

I often find people giving example of foo company using foo tools / technology and are doing great job scaling their overall architecture.

People often give example of Google, Yahoo! and Facebook when they have to make points about SQL and NoSQL but it is also to be considered that these companies are being able to scale with such an efficiency by not using only SQL or only using NoSQL technology.

Google, for example uses its BigTable, a column based database technology (one of the instances of NoSQL horizon) for indexing the web while they also use MySQL in significant ratio, in fact they have also provided patches for MySQL. And same is true for Facebook and Yahoo!.

Databases are hammers; MapReduce is a screwdriver

The article is quite interesting read differentiating normal databases (SQL) and MapReduce, a Google developed technology for aggregating large sets of data in distributed environment which is also used by number of NoSQL technologies like: MongoDB, CouchDB and many others.

I think the same concept can be used for SQL and NoSQL.

SQL is a hammer while NoSQL is a screwdriver

So, instead of ranting which is superior to each other, it would be better to combine them both and use them to create scalable + robust architecture. And Technology Agnostic design and Technology Agnostic Architecture (that include database in abstract term i.e. using SQL and/or NoSQL as demand by the context) are the most important things to consider when talking about scalability.

Update: When people used the term NoSQL, it would be better if they mean Not Only SQL rather than No SQL.

Excerpt from The Art of Scalability Chapter 27,  Too Much Data

1. Storage costs to store data
2. People and software to manage data
3. Power and space to make storage work
4. Capital to ensure the proper power infrastructure
5. Processing power to traverse the data
6. Backup time and costs