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DBMS > Faircom EDGE vs. Ignite vs. JanusGraph vs. Kinetica

System Properties Comparison Faircom EDGE vs. Ignite vs. JanusGraph vs. Kinetica

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Editorial information provided by DB-Engines
NameFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonIgnite  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.A Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017Fully vectorized database across both GPUs and CPUs
Primary database modelKey-value store
Relational DBMS
Key-value store
Relational DBMS
Graph DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Score3.11
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score2.02
Rank#125  Overall
#12  Graph DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Websitewww.faircom.com/­products/­faircom-edgeignite.apache.orgjanusgraph.orgwww.kinetica.com
Technical documentationdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlapacheignite.readme.io/­docsdocs.janusgraph.orgdocs.kinetica.com
DeveloperFairCom CorporationApache Software FoundationLinux Foundation; originally developed as Titan by AureliusKinetica
Initial release1979201520172012
Current releaseV3, October 2020Apache Ignite 2.60.6.3, February 20237.1, August 2021
License infoCommercial or Open Sourcecommercial infoRestricted, free version availableOpen Source infoApache 2.0Open Source infoApache 2.0commercial
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++C++, Java, .NetJavaC, C++
Server operating systemsAndroid
Linux infoARM, x86
Raspbian
Windows
Linux
OS X
Solaris
Windows
Linux
OS X
Unix
Windows
Linux
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.yesyesnono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyes infoANSI SQL queriesANSI-99 for query and DML statements, subset of DDLnoSQL-like DML and DDL statements
APIs and other access methodsADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C#
C++
Java
PHP
Python
Ruby
Scala
Clojure
Java
Python
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++yes (compute grid and cache interceptors can be used instead)yesuser defined functions
Triggersyesyes (cache interceptors and events)yesyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesFile partitioning infoCustomizable business rules for partitioningShardingyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoSynchronous and asynchronous realtime replication based on transaction logsyes (replicated cache)yesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)yes infovia Faunus, a graph analytics engineno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Tunable Consistency
Immediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes infowhen using SQLnoyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayes infoacross SQL and NoSQLyesyesyes
Durability infoSupport for making data persistentyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Security Hooks for custom implementationsUser authentification and security via Rexster Graph ServerAccess rights for users and roles on table level

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More resources
Faircom EDGE infoformerly c-treeEDGEIgniteJanusGraph infosuccessor of TitanKinetica
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