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DBMS > Faircom EDGE vs. FatDB vs. Google Cloud Bigtable vs. mSQL vs. Tkrzw

System Properties Comparison Faircom EDGE vs. FatDB vs. Google Cloud Bigtable vs. mSQL vs. Tkrzw

Editorial information provided by DB-Engines
NameFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsA .NET NoSQL DBMS that can integrate with and extend SQL Server.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.mSQL (Mini SQL) is a simple and lightweight RDBMSA 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 modelKey-value store
Relational DBMS
Document store
Key-value store
Key-value store
Wide column store
Relational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score1.27
Rank#167  Overall
#77  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitewww.faircom.com/­products/­faircom-edgecloud.google.com/­bigtablehughestech.com.au/­products/­msqldbmx.net/­tkrzw
Technical documentationdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlcloud.google.com/­bigtable/­docs
DeveloperFairCom CorporationFatCloudGoogleHughes TechnologiesMikio Hirabayashi
Initial release19792012201519942020
Current releaseV3, October 20204.4, October 20210.9.3, August 2020
License infoCommercial or Open Sourcecommercial infoRestricted, free version availablecommercialcommercialcommercial infofree licenses can be providedOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageANSI C, C++C#CC++
Server operating systemsAndroid
Linux infoARM, x86
Raspbian
Windows
WindowshostedAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Linux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyes, ANSI Standard SQL Typesyesnoyesno
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.yesnonono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyes infoANSI SQL queriesno infoVia inetgration in SQL ServernoA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggersno
APIs and other access methodsADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Supported programming languagesC
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C#C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C++
Delphi
Java
Perl
PHP
Tcl
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++yes infovia applicationsnonono
Triggersyesyes infovia applicationsnonono
Partitioning methods infoMethods for storing different data on different nodesFile partitioning infoCustomizable business rules for partitioningShardingShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoSynchronous and asynchronous realtime replication based on transaction logsselectable replication factorInternal replication in Colossus, and regional replication between two clusters in different zonesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Tunable Consistency
Eventual Consistency
Immediate Consistency
Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)noneImmediate Consistency
Foreign keys infoReferential integrityyes infowhen using SQLnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoAtomic single-row operationsno
Concurrency infoSupport for concurrent manipulation of datayes infoacross SQL and NoSQLyesyesnoyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes infousing specific database classes
User concepts infoAccess controlFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.no infoCan implement custom security layer via applicationsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nono

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More resources
Faircom EDGE infoformerly c-treeEDGEFatDBGoogle Cloud BigtablemSQL infoMini SQLTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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