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DBMS > Amazon DocumentDB vs. Faircom EDGE vs. RDF4J vs. Splice Machine

System Properties Comparison Amazon DocumentDB vs. Faircom EDGE vs. RDF4J vs. Splice Machine

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSplice Machine  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 environmentsRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument storeKey-value store
Relational DBMS
RDF storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteaws.amazon.com/­documentdbwww.faircom.com/­products/­faircom-edgerdf4j.orgsplicemachine.com
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlrdf4j.org/­documentationsplicemachine.com/­how-it-works
DeveloperFairCom CorporationSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Splice Machine
Initial release2019197920042014
Current releaseV3, October 20203.1, March 2021
License infoCommercial or Open Sourcecommercialcommercial infoRestricted, free version availableOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoAGPL 3.0, commercial license available
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++JavaJava
Server operating systemshostedAndroid
Linux infoARM, x86
Raspbian
Windows
Linux
OS X
Unix
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yes infoRDF Schemasyes
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.noyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnoyes infoANSI SQL queriesnoyes
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
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
JDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
Java
PHP
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++yesyes infoJava
Triggersnoyesyesyes
Partitioning methods infoMethods for storing different data on different nodesnoneFile partitioning infoCustomizable business rules for partitioningnoneShared Nothhing Auto-Sharding, Columnar Partitioning
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 logsnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nonoYes, via Full Spark Integration
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 SQLyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infoin-memory storage is supported as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlAccess rights for users and rolesFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.noAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon DocumentDBFaircom EDGE infoformerly c-treeEDGERDF4J infoformerly known as SesameSplice Machine
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