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DBMS > Faircom DB vs. NSDb vs. OrigoDB vs. Spark SQL vs. Transbase

System Properties Comparison Faircom DB vs. NSDb vs. OrigoDB vs. Spark SQL vs. Transbase

Editorial information provided by DB-Engines
NameFaircom DB infoformerly c-treeACE  Xexclude from comparisonNSDb  Xexclude from comparisonOrigoDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesA fully ACID in-memory object graph databaseSpark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelKey-value store
Relational DBMS
Time Series DBMSDocument store
Object oriented DBMS
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.24
Rank#311  Overall
#44  Key-value stores
#140  Relational DBMS
Score0.00
Rank#396  Overall
#42  Time Series DBMS
Score0.03
Rank#378  Overall
#51  Document stores
#18  Object oriented DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score0.15
Rank#337  Overall
#147  Relational DBMS
Websitewww.faircom.com/­products/­faircom-dbnsdb.ioorigodb.comspark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlnsdb.io/­Architectureorigodb.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperFairCom CorporationRobert Friberg et alApache Software FoundationTransaction Software GmbH
Initial release197920172009 infounder the name LiveDB20141987
Current releaseV12, November 20203.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open Sourcecommercial infoRestricted, free version availableOpen Source infoApache Version 2.0Open SourceOpen Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageANSI C, C++Java, ScalaC#ScalaC and C++
Server operating systemsAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
macOS
Linux
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeschema free, schema optional, schema required, partial schema,yesyesyes
Typing infopredefined data types such as float or dateyes, ANSI SQL Types, JSON, typed binary structuresyes: int, bigint, decimal, stringUser defined using .NET types and collectionsyesyes
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.nonono infocan be achieved using .NETnono
Secondary indexesyesall fields are automatically indexedyesnoyes
SQL infoSupport of SQLyes, ANSI SQL with proprietary extensionsSQL-like query languagenoSQL-like DML and DDL statementsyes
APIs and other access methodsADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
gRPC
HTTP REST
WebSocket
.NET Client API
HTTP API
LINQ
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languages.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
Java
Scala
.NetJava
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++noyesnoyes
Triggersyesyes infoDomain Eventsnoyes
Partitioning methods infoMethods for storing different data on different nodesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningShardinghorizontal partitioning infoclient side managed; servers are not synchronizedyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).Source-replica replicationnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnodepending on modelnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datatunable from ACID to Eventually ConsistentnoACIDnoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentYes, tunable from durable to delayed durability to in-memoryUsing Apache Luceneyes infoWrite ahead logyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnono
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filesRole based authorizationnofine grained access rights according to SQL-standard

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More resources
Faircom DB infoformerly c-treeACENSDbOrigoDBSpark SQLTransbase
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