Mean

(redirected from MongoDB)
Also found in: Dictionary, Medical, Encyclopedia.

MEAN. This word is sometimes used for mesne. (q.v.)

References in periodicals archive ?
R2M is built to enable automated migration to MongoDB thats 40-50 percent easier and faster whether the user is an expert in database server administration or not.
Informix also extends the MongoDB programming interface to allow relational data to be accessed through the same API.
MongoDB said subscription revenue was up 71% and services revenue was up 15% compared to a year ago.
The acquisition of Realm, the company behind the Realm mobile database and synchronisation platform, will deepen MongoDB's relationship with developer communities focussed on mobile and serverless development.
The new plug-in for MongoDB enables queries from MongoDB of JSON-LD serialized data.
ScaleGrid, a rising provider of database hosting and management, has announced the availability of fully managed MongoDB Hosting on Azure Government Cloud, the company said.
Obviously, MongoDB has done well enough in gathering the loyalty and affection of modern developers.
RDX supports a wide range of cloud environments including Microsoft Azure, Amazon AWS, and Oracle DB Cloud; database environments including Oracle, SQL Server, MYSQL, PostgreSQL, DB2 and MongoDB; and operating systems including Windows and all major UNIX/Linux offerings.
In this study, a MIBD-processing and MIBD-archiving middle layer platform based on Hadoop and MongoDB architecture has been developed.
"To recover your lost data: Send 0.2 BTC to our BitCoin Address and Contact us by email with your MongoDB server IP Address and a Proof of Payment.
In January 2017, CyberJack's research team detected and analyzed a coordinated attack on MongoDB, a specific type of database provider, exploiting a vulnerability in its latest version.
It provides theoretical explanations for new systems, techniques, and databases like GFS and HDFS (Google and Hadoop file systems), MapReduce, Cassandra, Neo4j, and MongoDB; outlines traditional algorithms like mergesort, B-trees, and hashing; discusses the foundations of different technologies and use cases for them; and details physical storage hardware like hard disk drives, solid-state drives, and magnetoresistive RAM to understand how they function and affect the complexity, performance, and capabilities of existing storage and analytics algorithms.