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

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

Editorial information provided by DB-Engines
NameEJDB  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonFatDB  Xexclude from comparisonSplice Machine  Xexclude from comparisonTeradata  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
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 SparkA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelDocument storeKey-value store
Relational DBMS
Document store
Key-value store
Relational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Time Series 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
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websitegithub.com/­Softmotions/­ejdbwww.faircom.com/­products/­faircom-edgesplicemachine.comwww.teradata.com
Technical documentationgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mddocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlsplicemachine.com/­how-it-worksdocs.teradata.com
DeveloperSoftmotionsFairCom CorporationFatCloudSplice MachineTeradata
Initial release20121979201220141984
Current releaseV3, October 20203.1, March 2021Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoGPLv2commercial infoRestricted, free version availablecommercialOpen Source infoAGPL 3.0, commercial license availablecommercial
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#Java
Server operating systemsserver-lessAndroid
Linux infoARM, x86
Raspbian
Windows
WindowsLinux
OS X
Solaris
Windows
hosted
Linux
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.yesyes
Secondary indexesnoyesyesyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLnoyes infoANSI SQL queriesno infoVia inetgration in SQL Serveryesyes infoSQL 2016 + extensions
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
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
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
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++yes infovia applicationsyes infoJavayes infoUDFs, stored procedures, table functions in parallel
Triggersnoyesyes infovia applicationsyesyes
Partitioning methods infoMethods for storing different data on different nodesnoneFile partitioning infoCustomizable business rules for partitioningShardingShared Nothhing Auto-Sharding, Columnar PartitioningSharding infoHashing
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
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Tunable Consistency
Eventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not needed, however similar functionality with collection joins possibleyes infowhen using SQLnoyesyes
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
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
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-standardfine grained access rights according to SQL-standard

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More resources
EJDBFaircom EDGE infoformerly c-treeEDGEFatDBSplice MachineTeradata
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