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DBMS > EJDB vs. Faircom EDGE vs. FatDB vs. Splice Machine vs. Titan

System Properties Comparison EJDB vs. Faircom EDGE vs. FatDB vs. Splice Machine vs. Titan

Editorial information provided by DB-Engines
NameEJDB  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonFatDB  Xexclude from comparisonSplice Machine  Xexclude from comparisonTitan  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.
DescriptionEmbeddable document-store database library with JSON representation of queries (in MongoDB style)FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsA .NET NoSQL DBMS that can integrate with and extend SQL Server.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkTitan is a Graph DBMS optimized for distributed clusters.
Primary database modelDocument storeKey-value store
Relational DBMS
Document store
Key-value store
Relational DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.27
Rank#297  Overall
#44  Document stores
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitegithub.com/­Softmotions/­ejdbwww.faircom.com/­products/­faircom-edgesplicemachine.comgithub.com/­thinkaurelius/­titan
Technical documentationgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mddocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlsplicemachine.com/­how-it-worksgithub.com/­thinkaurelius/­titan/­wiki
DeveloperSoftmotionsFairCom CorporationFatCloudSplice MachineAurelius, owned by DataStax
Initial release20121979201220142012
Current releaseV3, October 20203.1, March 2021
License infoCommercial or Open SourceOpen Source infoGPLv2commercial infoRestricted, free version availablecommercialOpen Source infoAGPL 3.0, commercial license availableOpen Source infoApache license, version 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCANSI C, C++C#JavaJava
Server operating systemsserver-lessAndroid
Linux infoARM, x86
Raspbian
Windows
WindowsLinux
OS X
Solaris
Windows
Linux
OS X
Unix
Windows
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesyes
Typing infopredefined data types such as float or dateyes infostring, integer, double, bool, date, object_idyes, 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.yes
Secondary indexesnoyesyesyesyes
SQL infoSupport of SQLnoyes infoANSI SQL queriesno infoVia inetgration in SQL Serveryesno
APIs and other access methodsin-process shared libraryADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
Native Spark Datasource
ODBC
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Supported programming languagesActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C#C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Clojure
Java
Python
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++yes infovia applicationsyes infoJavayes
Triggersnoyesyes infovia applicationsyesyes
Partitioning methods infoMethods for storing different data on different nodesnoneFile partitioning infoCustomizable business rules for partitioningShardingShared Nothhing Auto-Sharding, Columnar Partitioningyes infovia pluggable storage backends
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes infoSynchronous and asynchronous realtime replication based on transaction logsselectable replication factorMulti-source replication
Source-replica replication
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesYes, via Full Spark Integrationyes infovia Faunus, a graph analytics engine
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Tunable Consistency
Eventual Consistency
Immediate Consistency
Immediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityno infotypically not needed, however similar functionality with collection joins possibleyes infowhen using SQLnoyesyes infoRelationships in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/Write Lockingyes infoacross SQL and NoSQLyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlnoFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.no infoCan implement custom security layer via applicationsAccess rights for users, groups and roles according to SQL-standardUser authentification and security via Rexster Graph Server

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More resources
EJDBFaircom EDGE infoformerly c-treeEDGEFatDBSplice MachineTitan
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