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DBMS > Amazon DocumentDB vs. atoti vs. Faircom EDGE vs. Lovefield vs. Tkrzw

System Properties Comparison Amazon DocumentDB vs. atoti vs. Faircom EDGE vs. Lovefield vs. Tkrzw

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonatoti  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonLovefield  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsEmbeddable relational database for web apps written in pure JavaScriptA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelDocument storeObject oriented DBMSKey-value store
Relational DBMS
Relational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score0.56
Rank#245  Overall
#10  Object oriented DBMS
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score0.29
Rank#293  Overall
#133  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websiteaws.amazon.com/­documentdbatoti.iowww.faircom.com/­products/­faircom-edgegoogle.github.io/­lovefielddbmx.net/­tkrzw
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.atoti.iodocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.md
DeveloperActiveViamFairCom CorporationGoogleMikio Hirabayashi
Initial release2019197920142020
Current releaseV3, October 20202.1.12, February 20170.9.3, August 2020
License infoCommercial or Open Sourcecommercialcommercial infofree versions availablecommercial infoRestricted, free version availableOpen Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaANSI C, C++JavaScriptC++
Server operating systemshostedAndroid
Linux infoARM, x86
Raspbian
Windows
server-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariLinux
macOS
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yesschema-free
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesyesno
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.noyesnono
Secondary indexesyesyesyes
SQL infoSupport of SQLnoMultidimensional Expressions (MDX)yes infoANSI SQL queriesSQL-like query language infovia JavaScript builder patternno
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
JavaScriptC++
Java
Python
Ruby
Server-side scripts infoStored proceduresnoPythonyes info.Net, JavaScript, C/C++nono
TriggersnoyesUsing read-only observersno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding, horizontal partitioningFile partitioning infoCustomizable business rules for partitioningnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyes infoSynchronous and asynchronous realtime replication based on transaction logsnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyes infowhen using SQLyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yes infoacross SQL and NoSQLyesyes
Durability infoSupport for making data persistentyesyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes infousing MemoryDByes infousing specific database classes
User concepts infoAccess controlAccess rights for users and rolesFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.nono

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More resources
Amazon DocumentDBatotiFaircom EDGE infoformerly c-treeEDGELovefieldTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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