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DBMS > EsgynDB vs. Faircom EDGE vs. Hive vs. Kinetica vs. Teradata Aster

System Properties Comparison EsgynDB vs. Faircom EDGE vs. Hive vs. Kinetica vs. Teradata Aster

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonHive  Xexclude from comparisonKinetica  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.
DescriptionEnterprise-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 environmentsdata warehouse software for querying and managing large distributed datasets, built on HadoopFully vectorized database across both GPUs and CPUsPlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websitewww.esgyn.cnwww.faircom.com/­products/­faircom-edgehive.apache.orgwww.kinetica.com
Technical documentationdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.kinetica.com
DeveloperEsgynFairCom CorporationApache Software Foundation infoinitially developed by FacebookKineticaTeradata
Initial release20151979201220122005
Current releaseV3, October 20203.1.3, April 20227.1, August 2021
License infoCommercial or Open Sourcecommercialcommercial infoRestricted, free version availableOpen Source infoApache Version 2commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaANSI C, C++JavaC, C++
Server operating systemsLinuxAndroid
Linux infoARM, x86
Raspbian
Windows
All OS with a Java VMLinuxLinux
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesyesFlexible 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 Typesyesyesyes
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.noyesnoyes infoin Aster File Store
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLyesyes infoANSI SQL queriesSQL-like DML and DDL statementsSQL-like DML and DDL statementsyes
APIs and other access methodsADO.NET
JDBC
ODBC
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JDBC
ODBC
Thrift
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C++
Java
PHP
Python
C++
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresJava Stored Proceduresyes info.Net, JavaScript, C/C++yes infouser defined functions and integration of map-reduceuser defined functionsR packages
Triggersnoyesnoyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesShardingFile partitioning infoCustomizable business rules for partitioningShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersyes infoSynchronous and asynchronous realtime replication based on transaction logsselectable replication factorSource-replica replicationyes 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 methodsyesnoyes infoquery execution via MapReducenoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Tunable Consistency
Eventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesyes infowhen using SQLnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoGPU vRAM or System RAMno
User concepts infoAccess controlfine grained access rights according to SQL-standardFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Access rights for users, groups and rolesAccess rights for users and roles on table levelfine grained access rights according to SQL-standard

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More resources
EsgynDBFaircom EDGE infoformerly c-treeEDGEHiveKineticaTeradata Aster
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