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A distributed database is a database in which data is stored across different physical locations. [1] It may be stored in multiple computers located in the same physical location (e.g. a data centre); or maybe dispersed over a network of interconnected computers.
A distributed SQL database is a single relational database which replicates data across multiple servers. Distributed SQL databases are strongly consistent and most support consistency across racks, data centers, and wide area networks including cloud availability zones and cloud geographic zones .
The tradeoff between availability, consistency and latency, as described by the PACELC theorem. In database theory, the PACELC theorem is an extension to the CAP theorem.It states that in case of network partitioning (P) in a distributed computer system, one has to choose between availability (A) and consistency (C) (as per the CAP theorem), but else (E), even when the system is running ...
In database theory, the CAP theorem, also named Brewer's theorem after computer scientist Eric Brewer, states that any distributed data store can provide only two of the following three guarantees: [1] [2] [3]
Redis is a distributed, highly available, and scalable in-memory database with a "CRDT-enabled database" feature. [27] SoundCloud open-sourced Roshi, a LWW-element-set CRDT for the SoundCloud stream implemented on top of Redis. [28] Riak is a distributed NoSQL key-value data store based on CRDTs. [29]
A distributed data store is a computer network where information is stored on more than one node, often in a replicated fashion. [1] It is usually specifically used to refer to either a distributed database where users store information on a number of nodes , or a computer network in which users store information on a number of peer network nodes .
Dynamo is a set of techniques that together can form a highly available key-value structured storage system [1] or a distributed data store. [1] It has properties of both databases and distributed hash tables (DHTs). It was created to help address some scalability issues that Amazon experienced during the holiday season of 2004. [2]
In practice most commercial database systems use strong strict two-phase locking (SS2PL) for concurrency control, which ensures global serializability, if all the participating databases employ it. A common algorithm for ensuring correct completion of a distributed transaction is the two-phase commit (2PC).