MarkLogic Server

MarkLogic Server
Developer(s) MarkLogic
Written in C++, C and JavaScript
Available in English
Type Document-oriented database

MarkLogic Server is a document-oriented database developed by MarkLogic Corporation. It is a multi-model NoSQL database that has evolved from its XML database roots to also natively store JSON documents and RDF triples, the data model for semantics. MarkLogic is designed to be a data hub for operational and analytical data. [1]

History

MarkLogic Server was built to address shortcomings with existing search and data products.The product first focused on using XML document markup standard and XQuery as the query standard for accessing collections of documents up to hundreds of terabytes in size.

Current the database platform is widely used in publishing, government, finance and other sectors. [1] MarkLogic's customers are mostly Global 2000 companies.

Technology

MarkLogic uses documents without upfront schemas to maintaining a flexible data model. In addition to having a flexible data model, MarkLogic uses a distributed, scale-out architecture that can handle hundreds of billions of documents and hundreds of Terabytes of data. It has received Common Criteria certification, and has high availability and disaster recovery. MarkLogic is designed to run on-premises within public or private cloud environments like Amazon Web Services.

Main Features

Indexing

MarkLogic indexes the content and structure of documents including words, phrases, relationships, and values in over 200 languages with tokenization, collation, and stemming for core languages. Functionality includes ability to toggle range indexes, geospatial indexes, the triple index, and reverse indexes on or off based on your data, the kinds of queries that you will run, and your desired performance.

Full-text search

MarkLogic supports search across all of data using a word or phrase and rely on Boolean logic, stemming, wildcards, case sensitivity, punctuation sensitivity, diacritic sensitivity, and search term weighting. Search data using JavaScript, XQuery, SPARQL, and SQL.

Semantics

MarkLogic uses RDF triples to provide semantics for ease of storing meta data and querying.

ACID

Unlike other NoSQL databases, MarkLogic maintains ACID consistency for transactions.

Replication

MarkLogic provides high availability with replica sets.

Scalability

MarkLogic scales horizontally using sharding.

MarkLogic can run over multiple servers, balancing the load or duplicating data to keep the system up and running in case of hardware failure.

Security

MarkLogic has built in security features such as element-level permissions and redactions.

Optic API for Relational Operations

API that lets developers view their data as documents, graphs or rows. [1]

Security

MarkLogic provides redaction, encryption, and element-level security(allowing for control on read and write rights on parts of a document). [2]

Applications

Licensing

MarkLogic is available under various licensing and delivery models, namely a free Developer or an Essential Enterprise license.[3] Licenses are available from MarkLogic or directly from cloud marketplaces such as Amazon Web Services and Microsoft Azure.

Releases

  • 2003—Cerisent XQE 1.0
  • 2004—Cerisent XQE 2.0
  • 2005—MarkLogic Server 3.0
  • 2006—MarkLogic Server 3.1
  • 2007—MarkLogic Server 3.2
  • 2008—MarkLogic Server 4.0
  • 2009—MarkLogic Server 4.1
  • 2010—MarkLogic Server 4.2
  • 2011—MarkLogic Server 5.0
  • 2012—MarkLogic Server 6.0
  • 2013—MarkLogic Server 7.0
  • 2015—MarkLogic Server 8.0: Ability to store JSON data and process data using JavaScript.[3]
  • 2017—MarkLogic Server 9.0: Data integration across Relational and Non-Relational data.

See also

References

  1. 1 2 3 4 "MarkLogic Adds Element-level Security to Its NoSQL Database". eWEEK. Retrieved 2018-03-21.
  2. ↑ "Key steps to keeping data information safe - SD Times". SD Times. 2018-02-21. Retrieved 2018-03-21.
  3. ↑ "MarkLogic 4.0 Introduces Stable of New Features for the XML Server". Information Today. 9 October 2008. Retrieved 27 January 2015.
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