Database sharding, the "shared-nothing" approach database sharding

W smash a single database on a single server into a single database on multiple servers

http://www.agildata.com/database-sharding/

Database Sharding provides a method for scalability across independent servers, each with their own CPU, memory and disk. Contrasted with other traditional methods of achieving greater database performance, it does no suffer from many of the T Ypical limitations posed by these and other approaches. The concept of a "shared-nothing" database implementation has been under in the or discussion for 15+ years, but it AppE ARS, the business application, just now finding the more general need for such capability due to the exponent ial increase in data volumes over the past several years.

The basic concept of database sharding is very straightforward:take a large Database, and break it into a number of small ER databases across servers. The concept is illustrated in the following diagram:

Figure 2. Database sharding takes large databases and breaks them down into smaller databases.

The obvious advantage of the shared-nothing Database sharding approach are improved scalability, growing in a near-linear f Ashion as more servers is added to the network. However, there is several other advantages of smaller databases, which should not being overlooked when considering a Shardi NG Solution:

• Smaller databases is easier to manage.  production databases must is fully managed for regular backups, database optimization and other common tasks. With a single large database these routine tasks can is very difficult to accomplish if only in terms of the time window Required for completion. Routine table and Index optimizations can stretch to hours or days, in some cases making regular maintenance infeasible. By using the sharding approach, each individual "shard" can is maintained independently, providing a far more manageable s Cenario, performing such maintenance tasks in parallel.
• Smaller databases is faster.  the scalability of sharding is apparent, achieved through the distribution of processing across multiple shards and Servers in the network. What's less apparent are the fact that each individual shard database would outperform a single large database due to its s Maller size. By hosting all Shard database on its own server, the ratio between memory and data on disk is greatly improved, thereby r educing disk I/O. This results is contention for resources, greater join performance, faster index searches, and fewer database locks. Therefore, not only can a sharded system scale to new levels of capacity, individual transaction performance is benefited as well.
• Database sharding can reduce costs. Most Database sharding implementations take advantage of the Lower-cost open source databases, or can even take advantage of " Workgroup "versions of commercial databases. Additionally, sharding works well and commodity multi-core server hardware, far less expensive than high-end multi-cpu SE RVers and expensive SANs. The overall reduction in cost due to savings in license fees, software maintenance and hardware investment are substantial, In some cases 70% or more when compared to other solutions.

There is no doubt this Database sharding is a viable solution for many organizations, supported by the number of large onl INE vendors and SaaS organizations that has implemented the technology (giants such as Amazon, EBay, and of course Google ).

Database sharding, the "shared-nothing" approach database sharding