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DBMS > Amazon Neptune vs. Faircom EDGE vs. mSQL vs. Spark SQL

System Properties Comparison Amazon Neptune vs. Faircom EDGE vs. mSQL vs. Spark SQL

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsmSQL (Mini SQL) is a simple and lightweight RDBMSSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelGraph DBMS
RDF store
Key-value store
Relational DBMS
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Score1.27
Rank#169  Overall
#76  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­neptunewww.faircom.com/­products/­faircom-edgehughestech.com.au/­products/­msqlspark.apache.org/­sql
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonFairCom CorporationHughes TechnologiesApache Software Foundation
Initial release2017197919942014
Current releaseV3, October 20204.4, October 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercial infoRestricted, free version availablecommercial infofree licenses can be providedOpen Source infoApache 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++CScala
Server operating systemshostedAndroid
Linux infoARM, x86
Raspbian
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)yesyes
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesyesyes
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 indexesnoyesyesno
SQL infoSupport of SQLnoyes infoANSI SQL queriesA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggersSQL-like DML and DDL statements
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JDBC
ODBC
JDBC
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C
C++
Delphi
Java
Perl
PHP
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++nono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesnoneFile partitioning infoCustomizable business rules for partitioningnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.yes infoSynchronous and asynchronous realtime replication based on transaction logsnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Tunable Consistency
none
Foreign keys infoReferential integrityyes infoRelationships in graphsyes infowhen using SQLnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLnoyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.nono

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More resources
Amazon NeptuneFaircom EDGE infoformerly c-treeEDGEmSQL infoMini SQLSpark SQL
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