archy22
06-02-2011, 05:01 AM
1: Elastic scaling
For years, database administrators have relied on scale up — buying bigger servers as database load increases — rather than scale out — distributing the database across multiple hosts as load increases. However, as transaction rates and availability requirements increase, and as databases move into the cloud or onto virtualized environments, the economic advantages of scaling out on commodity hardware become irresistible.
2: Big data
Just as transaction rates have grown out of recognition over the last decade, the volumes of data that are being stored also have increased massively. O’Reilly has cleverly called this the “industrial revolution of data
3: Goodbye DBAs
Despite the many manageability improvements claimed by RDBMS vendors over the years, high-end RDBMS systems can be maintained only with the assistance of expensive, highly trained DBAs. DBAs are intimately involved in the design, installation, and ongoing tuning of high-end RDBMS systems.
4: Economics
NoSQL databases typically use clusters of cheap commodity servers to manage the exploding data and transaction volumes, while RDBMS tends to rely on expensive proprietary servers and storage systems.
5: Flexible data models
Change management is a big headache for large production RDBMS. Even minor changes to the data model of an RDBMS have to be carefully managed and may necessitate downtime or reduced service levels.
For years, database administrators have relied on scale up — buying bigger servers as database load increases — rather than scale out — distributing the database across multiple hosts as load increases. However, as transaction rates and availability requirements increase, and as databases move into the cloud or onto virtualized environments, the economic advantages of scaling out on commodity hardware become irresistible.
2: Big data
Just as transaction rates have grown out of recognition over the last decade, the volumes of data that are being stored also have increased massively. O’Reilly has cleverly called this the “industrial revolution of data
3: Goodbye DBAs
Despite the many manageability improvements claimed by RDBMS vendors over the years, high-end RDBMS systems can be maintained only with the assistance of expensive, highly trained DBAs. DBAs are intimately involved in the design, installation, and ongoing tuning of high-end RDBMS systems.
4: Economics
NoSQL databases typically use clusters of cheap commodity servers to manage the exploding data and transaction volumes, while RDBMS tends to rely on expensive proprietary servers and storage systems.
5: Flexible data models
Change management is a big headache for large production RDBMS. Even minor changes to the data model of an RDBMS have to be carefully managed and may necessitate downtime or reduced service levels.