When we face huge problems, scalability becomes an issue, and most algorithms are not applicable.
Although SMAP outperforms most existing ligand binding site comparison tools, it cannot achieve the high scalability and availability demanded by huge database searching.
Although BLASTP outperforms most existing local sequence alignment tools, it does not satisfy the need of high scalability and high availability for searching huge protein database.
He is investing over $1 billion of his clients' money in "black swans"—ideas with the potential for sudden jumps in technology that promise huge environmental benefits, easy scalability and rapid payback.
But to achieve efficiency, performance, and scalability for processing huge data, a highly parallel distributed computing model is required.
The rise of NoSQL databases [21] has attracted the attention of database community due to its flexibility in providing schema-later architecture and its scalability for handling huge amount of big data.
Backend as a Service (BaaS) is a common nomenclature for these utilities, and their popularity is guaranteed to rise, particularly in the enterprise space where scalability poses a huge burden for large applications.
The huge number of users leads to scalability problems as can be seen in several news articles (e.g., Twitter admitted that "record traffic" and "unprecedented spikes in activity" led to problems with the site[8]).
Cloud computing mainly adopts MapReduce as its parallel programming model, allowing numerous cheap commercial computers to be used for computing and giving high reliability, low cost, the capability for processing a huge amount of data, flexibility and scalability.
Do yourself a huge favor and start thinking about scalability and processes to systematize early on, even before your first flip.
