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DBMS > Amazon DocumentDB vs. Faircom DB vs. RDF4J vs. WakandaDB

System Properties Comparison Amazon DocumentDB vs. Faircom DB vs. RDF4J vs. WakandaDB

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelDocument storeKey-value store
Relational DBMS
RDF storeObject oriented DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websiteaws.amazon.com/­documentdbwww.faircom.com/­products/­faircom-dbrdf4j.orgwakanda.github.io
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlrdf4j.org/­documentationwakanda.github.io/­doc
DeveloperFairCom CorporationSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Wakanda SAS
Initial release2019197920042012
Current releaseV12, November 20202.7.0 (AprilĀ 29, 2019), April 2019
License infoCommercial or Open Sourcecommercialcommercial infoRestricted, free version availableOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoAGPLv3, extended 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++JavaC++, JavaScript
Server operating systemshostedAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
OS X
Unix
Windows
Linux
OS X
Windows
Data schemeschema-freeschema free, schema optional, schema required, partial schema,yes infoRDF Schemasyes
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresyesyes
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.nonono
Secondary indexesyesyesyes
SQL infoSupport of SQLnoyes, ANSI SQL with proprietary extensionsnono
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
RESTful HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
Java
PHP
Python
JavaScript
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++yesyes
Triggersnoyesyesyes
Partitioning methods infoMethods for storing different data on different nodesnoneFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationstunable from ACID to Eventually ConsistentACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesYes, tunable from durable to delayed durability to in-memoryyes 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.yesno
User concepts infoAccess controlAccess rights for users and rolesFine grained access rights according to SQL-standard with additional protections for filesnoyes

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More resources
Amazon DocumentDBFaircom DB infoformerly c-treeACERDF4J infoformerly known as SesameWakandaDB
Recent citations in the news

Reduce cost and improve performance by migrating to Amazon DocumentDB 5.0 | Amazon Web Services
15 April 2024, AWS Blog

Vector search for Amazon DocumentDB (with MongoDB compatibility) is now generally available | Amazon Web Services
29 November 2023, AWS Blog

AWS announces Amazon DocumentDB I/O-Optimized
21 November 2023, AWS Blog

AWS announces vector search for Amazon DocumentDB
29 November 2023, AWS Blog

Mask sensitive Amazon DocumentDB log data with Amazon CloudWatch Logs data protection | Amazon Web Services
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FairCom kicks off new era of database technology USA - English
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