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DBMS > AnzoGraph DB vs. EsgynDB vs. Faircom EDGE vs. Teradata Aster

System Properties Comparison AnzoGraph DB vs. EsgynDB vs. Faircom EDGE vs. Teradata Aster

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Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonEsgynDB  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsPlatform for big data analytics on multistructured data sources and types
Primary database modelGraph DBMS
RDF store
Relational DBMSKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#307  Overall
#24  Graph DBMS
#13  RDF stores
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Websitecambridgesemantics.com/­anzographwww.esgyn.cnwww.faircom.com/­products/­faircom-edge
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html
DeveloperCambridge SemanticsEsgynFairCom CorporationTeradata
Initial release2018201519792005
Current release2.3, January 2021V3, October 2020
License infoCommercial or Open Sourcecommercial infofree trial version availablecommercialcommercial infoRestricted, free version availablecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaANSI C, C++
Server operating systemsLinuxLinuxAndroid
Linux infoARM, x86
Raspbian
Windows
Linux
Data schemeSchema-free and OWL/RDFS-schema supportyesFlexible Schema (defined schema, partial schema, schema free)Flexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesyes
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.nonoyesyes infoin Aster File Store
Secondary indexesnoyesyesyes
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.yesyes infoANSI SQL queriesyes
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
ADO.NET
JDBC
ODBC
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC++
Java
Python
All languages supporting JDBC/ODBC/ADO.NetC
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresuser defined functions and aggregatesJava Stored Proceduresyes info.Net, JavaScript, C/C++R packages
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingFile partitioning infoCustomizable business rules for partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-ClusterMulti-source replication between multi datacentersyes infoSynchronous and asynchronous realtime replication based on transaction logsyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingyesnoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterImmediate ConsistencyImmediate Consistency
Tunable Consistency
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityno infonot needed in graphsyesyes infowhen using SQLno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoacross SQL and NoSQLyes
Durability infoSupport for making data persistentyesyesyesyes
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 rolesfine grained access rights according to SQL-standardFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.fine grained access rights according to SQL-standard

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More resources
AnzoGraph DBEsgynDBFaircom EDGE infoformerly c-treeEDGETeradata Aster
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