Sharding is a database partitioning concept that is used to make databases more efficient. An organization’s network can be separated into smaller partitions which are known as “shards.” Each shard has its own distinctive and independent data when compared to other shards.
Sharding is a technique used to optimize the data stored and process it quickly and efficiently. It is a horizontal partitioning of a database, thereby separating the load on a single database and make it more efficient. Each shard is stored in a separate server instance. It helps achieve latency-free scalability by spreading the network workload into shards and enabling more transactions to be processed.
A decentralized database splits the workload up among multiple machines and uses sophisticated algorithms to balance the incoming and outgoing requests for the best response time. This type of database is useful for those times when there is more data that needs to be stored in the database than can physically saved on one physical machine. The bits — like log files, data collected by tracking click-throughs in the application, and the data generated by internet of things devices — pile up and need to be stored somewhere. They are also frequently referred to as distributed databases.
“If you’re trying to overcome a technology like relational databases, which have been developed over decades and had gestation from every major university in the world that does computer science research, it takes a long time to climb that hill,” Kreps says. “What’s very different for us is there hasn’t really been this incredibly well-developed infrastructure layer in the space we’re entering. We get to kind of make it up as we go along, which is a huge advantage. “
This perhaps is the reason why — despite the availability of MySQL, MariaDB, and PostgreSQL RDBMs, the advent of modern NoSQL and NewSQL solutions, and scalable Hadoop and object-storage alternatives — proprietary RDBMs continue to drive the lion’s share of enterprise spending in the data management space.
Phi Beta Iota: The time has come for a clean-sheet fresh start. The Internet was designed for machine to machine communication, it was never designed for humans or content. We process less than 1% of the Big Data we have in hand and that in turn is less than 1% of what is known. A post-Amazon post-Google Internet will be distributed and encrypted, including the 50% of humanity not on the Internet today, and enable paragraph level linking and weighting.