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DBMS > AnzoGraph DB vs. CouchDB vs. Faircom DB vs. Spark SQL

System Properties Comparison AnzoGraph DB vs. CouchDB vs. Faircom DB vs. Spark SQL

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NameAnzoGraph DB  Xexclude from comparisonCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationA native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelGraph DBMS
RDF store
Document storeKey-value store
Relational DBMS
Relational DBMS
Secondary database modelsSpatial DBMS infousing the Geocouch extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#307  Overall
#24  Graph DBMS
#13  RDF stores
Score9.30
Rank#45  Overall
#7  Document stores
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitecambridgesemantics.com/­anzographcouchdb.apache.orgwww.faircom.com/­products/­faircom-dbspark.apache.org/­sql
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmdocs.couchdb.org/­en/­stabledocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCambridge SemanticsApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerFairCom CorporationApache Software Foundation
Initial release2018200519792014
Current release2.3, January 20213.3.3, December 2023V12, November 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoApache version 2commercial infoRestricted, free version availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageErlangANSI C, C++Scala
Server operating systemsLinuxAndroid
BSD
Linux
OS X
Solaris
Windows
AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
OS X
Windows
Data schemeSchema-free and OWL/RDFS-schema supportschema-freeschema free, schema optional, schema required, partial schema,yes
Typing infopredefined data types such as float or datenoyes, ANSI SQL Types, JSON, typed binary structuresyes
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.nononono
Secondary indexesnoyes infovia viewsyesno
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.noyes, ANSI SQL with proprietary extensionsSQL-like DML and DDL statements
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
RESTful HTTP/JSON APIADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
JDBC
ODBC
Supported programming languagesC++
Java
Python
C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesView functions in JavaScriptyes info.Net, JavaScript, C/C++no
Triggersnoyesyesno
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingSharding infoimproved architecture with release 2.0File partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-ClusterMulti-source replication
Source-replica replication
yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).none
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterEventual ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Foreign keys infoReferential integrityno infonot needed in graphsnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infoatomic operations within a single document possibletunable from ACID to Eventually Consistentno
Concurrency infoSupport for concurrent manipulation of datayesyes infostrategy: optimistic lockingyesyes
Durability infoSupport for making data persistentyesyesYes, tunable from durable to delayed durability to in-memoryyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesno
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users can be defined per databaseFine grained access rights according to SQL-standard with additional protections for filesno

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More resources
AnzoGraph DBCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"Faircom DB infoformerly c-treeACESpark SQL
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