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Summary of NoSQL _1_ Summary of NoSQL _2_ A NoSQL taxonomy


NoSQL, refers to a non-relational database. With the rise of the Internet web2.0 site, the traditional relational database in dealing with web2.0 site, especially the large scale and high concurrent SNS type of web2.0 pure dynamic website has appeared to be inadequate, exposes a lot of difficult problems to overcome, rather than the relational database is characterized by its own has been very rapid development.

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Summary of NoSQL (1)                                                 Summary of NoSQL (2)
 NoSQL databases are non-relational, and tend to focus on the         With data replication, we encounter the problem of consistency
 problem of scalability. They accomplish this by avoiding shared      among the replicas. There is a trade-off between consistency
 resources.                                                           and availability of the database.
 To achieve scalability, NoSQL databases use sharding (divide the                                         databases,
                                                                      Joins are rarely efficient in NoSQL databases since the data
 data across different locations).                                    may be split across a number of machines.
 NoSQL databases often use some data replication, to achieve          MapReduce allows us to perform certain types of computation
 fault tolerance, geographic locality, and denormalization.           across sharded datasets.

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A NoSQL taxonomy                                                     Text search
 1.   Key/value stores                      (Kyoto Cabinet, Redis,
                                            Berkeley DB, etc.)
 2.   Document-based databases              (MongoDB, CouchDB,
                                            etc.                                                         SELECT *
                                                                                                         FROM WebPages
 3.   Column-oriented databases             (Cassandra, BigTable,
                                                                                                         WHERE content LIKE ‘%cats%’;
                                            C-store, etc.)
 4.   Text-search databases                 (Apache Solr, others)

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Forward indices                                                      Inverted indices

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“Full” inverted indices        Other text search goals

                                1. Relevancy ranking
                                2. Result highlighting
                                3. Query spell correction
                                3 Q           ll       ti
                                4. Sub-string indexing
                                5. Term auto-complete

                                … lots more!

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