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DBMS > atoti vs. Blueflood vs. MongoDB

System Properties Comparison atoti vs. Blueflood vs. MongoDB

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonBlueflood  Xexclude from comparisonMongoDB  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.Scalable TimeSeries DBMS based on CassandraOne of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure
Primary database modelObject oriented DBMSTime Series DBMSDocument store
Secondary database modelsSpatial DBMS
Search engine infointegrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS infoTime Series Collections introduced in Release 5.0
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.38
Rank#257  Overall
#15  Object oriented DBMS
Score0.16
Rank#297  Overall
#25  Time Series DBMS
Score496.50
Rank#5  Overall
#1  Document stores
Websitewww.atoti.ioblueflood.iowww.mongodb.com
Technical documentationgithub.com/­rackerlabs/­blueflood/­wikidocs.mongodb.com/­manual
DeveloperActiveViamRackspaceMongoDB, Inc
Initial release20132009
Current release5.0, July 2021
License infoCommercial or Open Sourcecommercial infofree versions availableOpen Source infoApache 2.0Open Source infoMongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.
Cloud-based only infoOnly available as a cloud servicenonono infoMongoDB available as DBaaS (MongoDB Atlas)
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
  • ScaleGrid for MongoDB: Fully managed hosting for MongoDB database on AWS, Azure and DigitalOcean with high availability and SSH access on the #1 multi-cloud DBaaS.
  • MongoDB Atlas: Global multi-cloud database with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more.
Implementation languageJavaJavaC++
Server operating systemsLinux
OS X
Linux
OS X
Solaris
Windows
Data schemepredefined schemeschema-free infoAlthough schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.
Typing infopredefined data types such as float or dateyesyes infostring, integer, double, decimal, boolean, date, object_id, geospatial
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.no
Secondary indexesnoyes
SQL infoSupport of SQLMultidimensional Expressions (MDX)noRead-only SQL queries via the MongoDB Connector for BI
APIs and other access methodsHTTP RESTproprietary protocol using JSON
Supported programming languagesActionscript infounofficial driver
C
C#
C++
Clojure infounofficial driver
ColdFusion infounofficial driver
D infounofficial driver
Dart infounofficial driver
Delphi infounofficial driver
Erlang
Go
Groovy infounofficial driver
Haskell
Java
JavaScript
Lisp infounofficial driver
Lua infounofficial driver
MatLab infounofficial driver
Perl
PHP
PowerShell infounofficial driver
Prolog infounofficial driver
Python
R infounofficial driver
Ruby
Rust
Scala
Smalltalk infounofficial driver
Swift
Server-side scripts infoStored proceduresPythonnoJavaScript
Triggersnoyes infoin MongoDB Atlas only
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningSharding infobased on CassandraSharding infoPartitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on CassandraMulti-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Immediate Consistency infocan be individually decided for each write operation
Foreign keys infoReferential integritynono infotypically not used, however similar functionality with DBRef possible
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoMulti-document ACID Transactions with snapshot isolation
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyes infooptional, enabled by default
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infoIn-memory storage engine introduced with MongoDB version 3.2
User concepts infoAccess controlnoAccess rights for users and roles
More information provided by the system vendor
atotiBluefloodMongoDB
Specific characteristicsMongoDB’s application data platform provides developers a unified interface to power...
» more
Competitive advantagesThe MongoDB platform can be used by developers building transactional, operational,...
» more
Typical application scenariosInternet of Things and Time Series (Bosch, Jaguar Land Rover) Mobile (The Weather...
» more
Key customersADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
» more
Market metrics175 million downloads, over 1.5M Atlas database clusters under management handling...
» more
Licensing and pricing modelsMongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
atotiBluefloodMongoDB
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