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DBMS > Amazon DocumentDB vs. Faircom EDGE vs. SingleStore vs. Tkrzw

System Properties Comparison Amazon DocumentDB vs. Faircom EDGE vs. SingleStore vs. Tkrzw

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsMySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table typeA 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 storeKey-value store
Relational DBMS
Relational DBMSKey-value store
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#124  Overall
#22  Document stores
Score0.02
Rank#370  Overall
#55  Key-value stores
#157  Relational DBMS
Score4.02
Rank#74  Overall
#39  Relational DBMS
Score0.00
Rank#385  Overall
#61  Key-value stores
Websiteaws.amazon.com/­documentdbwww.faircom.com/­products/­faircom-edgewww.singlestore.comdbmx.net/­tkrzw
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmldocs.singlestore.com
DeveloperFairCom CorporationSingleStore Inc.Mikio Hirabayashi
Initial release2019197920132020
Current releaseV3, October 20208.5, January 20240.9.3, August 2020
License infoCommercial or Open Sourcecommercialcommercial infoRestricted, free version availablecommercial infofree developer edition availableOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageANSI C, C++C++, GoC++
Server operating systemshostedAndroid
Linux infoARM, x86
Raspbian
Windows
Linux info64 bit version requiredLinux
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 SQLnoyes infoANSI SQL queriesyes infobut no triggers and foreign keysno
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
Cluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
Bash
C
C#
Java
JavaScript (Node.js)
Python
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++yesno
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesnoneFile partitioning infoCustomizable business rules for partitioningSharding infohash partitioningnone
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 logsSource-replica replication infostores two copies of each physical data partition on two separate nodesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nono infocan define user-defined aggregate functions for map-reduce-style calculationsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Tunable Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyes infowhen using SQLnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes 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.Fine grained access control via users, groups and rolesno

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More resources
Amazon DocumentDBFaircom EDGE infoformerly c-treeEDGESingleStore infoformer name was MemSQLTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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