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DBMS > ArcadeDB vs. Faircom EDGE vs. JanusGraph vs. mSQL vs. Spark SQL

System Properties Comparison ArcadeDB vs. Faircom EDGE vs. JanusGraph vs. mSQL vs. Spark SQL

Editorial information provided by DB-Engines
NameArcadeDB  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionFast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewrittenFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsA Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017mSQL (Mini SQL) is a simple and lightweight RDBMSSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Graph DBMS
Key-value store
Time Series DBMS infoin next version
Key-value store
Relational DBMS
Graph DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.10
Rank#358  Overall
#48  Document stores
#38  Graph DBMS
#52  Key-value stores
#35  Time Series DBMS
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Score2.02
Rank#125  Overall
#12  Graph DBMS
Score1.27
Rank#169  Overall
#76  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitearcadedb.comwww.faircom.com/­products/­faircom-edgejanusgraph.orghughestech.com.au/­products/­msqlspark.apache.org/­sql
Technical documentationdocs.arcadedb.comdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmldocs.janusgraph.orgspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperArcade DataFairCom CorporationLinux Foundation; originally developed as Titan by AureliusHughes TechnologiesApache Software Foundation
Initial release20211979201719942014
Current releaseSeptember 2021V3, October 20200.6.3, February 20234.4, October 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infoRestricted, free version availableOpen Source infoApache 2.0commercial infofree licenses can be providedOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaANSI C, C++JavaCScala
Server operating systemsAll OS with a Java VMAndroid
Linux infoARM, x86
Raspbian
Windows
Linux
OS X
Unix
Windows
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Linux
OS X
Windows
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yesyesyes
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesyesyesyes
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.noyesnonono
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLSQL-like query language, no joinsyes infoANSI SQL queriesnoA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggersSQL-like DML and DDL statements
APIs and other access methodsJDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
JDBC
ODBC
JDBC
ODBC
Supported programming languagesJavaC
C#
C++
Java
JavaScript
PHP
Python
VB.Net
Clojure
Java
Python
C
C++
Delphi
Java
Perl
PHP
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++yesnono
Triggersyesyesnono
Partitioning methods infoMethods for storing different data on different nodesFile partitioning infoCustomizable business rules for partitioningyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)noneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoSynchronous and asynchronous realtime replication based on transaction logsyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infovia Faunus, a graph analytics engineno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Tunable Consistency
Eventual Consistency
Immediate Consistency
none
Foreign keys infoReferential integrityyes inforelationship in graphsyes infowhen using SQLyes infoRelationships in graphsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesnoyes
Durability infoSupport for making data persistentyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.User authentification and security via Rexster Graph Servernono

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More resources
ArcadeDBFaircom EDGE infoformerly c-treeEDGEJanusGraph infosuccessor of TitanmSQL infoMini SQLSpark SQL
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