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DBMS > Faircom DB vs. Kinetica vs. NSDb vs. TimesTen vs. Tkrzw

System Properties Comparison Faircom DB vs. Kinetica vs. NSDb vs. TimesTen vs. Tkrzw

Editorial information provided by DB-Engines
NameFaircom DB infoformerly c-treeACE  Xexclude from comparisonKinetica  Xexclude from comparisonNSDb  Xexclude from comparisonTimesTen  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Fully vectorized database across both GPUs and CPUsScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesIn-Memory RDBMS compatible to OracleA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelKey-value store
Relational DBMS
Relational DBMSTime Series DBMSRelational DBMSKey-value store
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score1.31
Rank#163  Overall
#74  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitewww.faircom.com/­products/­faircom-dbwww.kinetica.comnsdb.iowww.oracle.com/­database/­technologies/­related/­timesten.htmldbmx.net/­tkrzw
Technical documentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmldocs.kinetica.comnsdb.io/­Architecturedocs.oracle.com/­database/­timesten-18.1
DeveloperFairCom CorporationKineticaOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005Mikio Hirabayashi
Initial release19792012201719982020
Current releaseV12, November 20207.1, August 202111 Release 2 (11.2.2.8.0)0.9.3, August 2020
License infoCommercial or Open Sourcecommercial infoRestricted, free version availablecommercialOpen Source infoApache Version 2.0commercialOpen Source infoApache 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 languageANSI C, C++C, C++Java, ScalaC++
Server operating systemsAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
LinuxLinux
macOS
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Linux
macOS
Data schemeschema free, schema optional, schema required, partial schema,yesyesschema-free
Typing infopredefined data types such as float or dateyes, ANSI SQL Types, JSON, typed binary structuresyesyes: int, bigint, decimal, stringyesno
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.nonononono
Secondary indexesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLyes, ANSI SQL with proprietary extensionsSQL-like DML and DDL statementsSQL-like query languageyesno
APIs and other access methodsADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
JDBC
ODBC
RESTful HTTP API
gRPC
HTTP REST
WebSocket
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languages.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C++
Java
JavaScript (Node.js)
Python
Java
Scala
C
C++
Java
PL/SQL
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++user defined functionsnoPL/SQLno
Triggersyesyes infotriggers when inserted values for one or more columns fall within a specified rangenono
Partitioning methods infoMethods for storing different data on different nodesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningShardingShardingnonenone
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 replicationMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate Consistency or Eventual Consistency depending on configurationEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datatunable from ACID to Eventually ConsistentnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentYes, tunable from durable to delayed durability to in-memoryyesUsing Apache Luceneyes infoby means of logfiles and checkpointsyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAMyesyes infousing specific database classes
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filesAccess rights for users and roles on table levelfine grained access rights according to SQL-standardno

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More resources
Faircom DB infoformerly c-treeACEKineticaNSDbTimesTenTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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