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DBMS > Faircom EDGE vs. Hive vs. HugeGraph vs. Splice Machine

System Properties Comparison Faircom EDGE vs. Hive vs. HugeGraph vs. Splice Machine

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Editorial information provided by DB-Engines
NameFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonHive  Xexclude from comparisonHugeGraph  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionFairCom 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 HadoopA fast-speed and highly-scalable Graph DBMSOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value store
Relational DBMS
Relational DBMSGraph DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.faircom.com/­products/­faircom-edgehive.apache.orggithub.com/­hugegraph
hugegraph.apache.org
splicemachine.com
Technical documentationdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlcwiki.apache.org/­confluence/­display/­Hive/­Homehugegraph.apache.org/­docssplicemachine.com/­how-it-works
DeveloperFairCom CorporationApache Software Foundation infoinitially developed by FacebookBaiduSplice Machine
Initial release1979201220182014
Current releaseV3, October 20203.1.3, April 20220.93.1, March 2021
License infoCommercial or Open Sourcecommercial infoRestricted, free version availableOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageANSI C, C++JavaJavaJava
Server operating systemsAndroid
Linux infoARM, x86
Raspbian
Windows
All OS with a Java VMLinux
macOS
Unix
Linux
OS X
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesyes
Typing infopredefined data types such as float or dateyes, 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.yesno
Secondary indexesyesyesyes infoalso supports composite index and range indexyes
SQL infoSupport of SQLyes infoANSI SQL queriesSQL-like DML and DDL statementsnoyes
APIs and other access methodsADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JDBC
ODBC
Thrift
Java API
RESTful HTTP API
TinkerPop Gremlin
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C++
Java
PHP
Python
Groovy
Java
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++yes infouser defined functions and integration of map-reduceasynchronous Gremlin script jobsyes infoJava
Triggersyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesFile partitioning infoCustomizable business rules for partitioningShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoSynchronous and asynchronous realtime replication based on transaction logsselectable replication factoryes infodepending on used storage backend, e.g. Cassandra and HBaseMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducevia hugegraph-sparkYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Tunable Consistency
Eventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infowhen using SQLnoyes infoedges in graphyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayes infoacross SQL and NoSQLyesyesyes, multi-version concurrency control (MVCC)
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.yesyesyes
User concepts infoAccess controlFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Access rights for users, groups and rolesUsers, roles and permissionsAccess rights for users, groups and roles according to SQL-standard

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More resources
Faircom EDGE infoformerly c-treeEDGEHiveHugeGraphSplice Machine
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