NoSQL: Difference between revisions
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===Column-oriented Databases=== | ===Column-oriented Databases=== | ||
The column oriented database stores entries by column as opposed to row-oriented databases. This optimizes the SQL databases by maximizing disk performance and making it easier to query many rows for smaller sets of data. | |||
Examples of open-source and commercial column oriented databases includes: Cassandra(Facebook), Big Table(Google), Hypertable(Open-source implementation of Big Table), Hbase(Open-source implementation of Big Table), etc. | |||
===Document-based Stores=== | ===Document-based Stores=== | ||
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NoSQL refers to a number of non-relational distributed database architectures. NoSQL architectures usually store data as key-value pairs, rather than supporting relations. Some systems eliminate the guarantee of consistency (instead promising eventual consistency) in order to increase scalability. The distributed nature of NoSQL architectures makes such data stores highly scalable and fault-tolerant.
History
NoSQL vs. RDBMS
In many cases, NoSQL databases can process data more quickly than traditional relational database management systems. One reason for this is that data representation in NoSQL databases is much simpler than in relational systems. For example, a table in a relational database might have many columns, but data in a key-value store will always have only two parts: the key and the value. In addition, many NoSQL databases do not fully support ACID transactions. While this allows faster performance, it can also be risky in applications where precision is needed, such as in banking applications.[1]
Disadvantages of NoSQL
Relationship to cloud computing
Types of NoSQL Databases
Key-value Store
A key-value store maintains data as a pair consisting of an indexed key and a value. In general, key-value stores provide a single operation: fetching a single value using its key. Some key-value store implementations include mechanisms for performing a join on two distinct tables. Examples of key-value stores include Oracle's BerkeleyDB and Amazon's Dynamo.
BerkeleyDB
BerkeleyDB is an open source, transactional, embedded database engine. It is available as a library that can be included in any application. Data are represented as key/value pairs. The keys and values in BerkeleyDB can be any objects supported by the programming language. Data are stored in files on disk, as a single file for each key-value store. BerkeleyDB also provides the option to maintain data stores in memory only, if the store is small enough to fit in main memory.
BerkeleyDB provides a number of features competitive with relational databases, including support for transactions, two-phase locking, joins, and write ahead logging. These features make BerkeleyDB very reliable. The BerkeleyDB engine is used in a number of applications. The MySQL database management system offers BerkeleyDB as an option for the storage engine.[2]
BerkeleyDB in itself does not provide a method for distributing data, but using a distributed hash table, it is possible to distribute data across multiple BerkeleyDB instances.
Dynamo
Column-oriented Databases
The column oriented database stores entries by column as opposed to row-oriented databases. This optimizes the SQL databases by maximizing disk performance and making it easier to query many rows for smaller sets of data.
Examples of open-source and commercial column oriented databases includes: Cassandra(Facebook), Big Table(Google), Hypertable(Open-source implementation of Big Table), Hbase(Open-source implementation of Big Table), etc.
Document-based Stores
Future perspective
References
- ↑ Leavitt, Neal, "Will NoSQL Databases Live Up to Their Promise?]", Computer
- ↑ Seltzer, Margo, "[www.usenix.org/event/usenix99/full_papers/olson/olson.pdf Berkeley DB]]", USENIX