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DBMS > FatDB vs. RavenDB vs. Splice Machine vs. TimesTen vs. Tkrzw

System Properties Comparison FatDB vs. RavenDB vs. Splice Machine vs. TimesTen vs. Tkrzw

Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonRavenDB  Xexclude from comparisonSplice Machine  Xexclude from comparisonTimesTen  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionA .NET NoSQL DBMS that can integrate with and extend SQL Server.Open Source Operational and Transactional Enterprise NoSQL Document DatabaseOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkAn in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.A 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 modelDocument store
Key-value store
Document storeRelational DBMSRelational DBMSKey-value store
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.68
Rank#102  Overall
#19  Document stores
Score0.54
Rank#244  Overall
#114  Relational DBMS
Score1.26
Rank#164  Overall
#75  Relational DBMS
Score0.00
Rank#385  Overall
#61  Key-value stores
Websiteravendb.netsplicemachine.comwww.oracle.com/­database/­technologies/­related/­timesten.htmldbmx.net/­tkrzw
Technical documentationravendb.net/­docssplicemachine.com/­how-it-worksdocs.oracle.com/­en/­database/­other-databases/­timesten/­index.html
DeveloperFatCloudHibernating RhinosSplice MachineOracle infooriginally founded in HP Labs it was acquired by Oracle in 2005Mikio Hirabayashi
Initial release20122010201419982020
Current release5.4, July 20223.1, March 2021Release 22.10.9.3, August 2020
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3, commercial license availableOpen Source infoAGPL 3.0, commercial license availablecommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#C#JavaC++
Server operating systemsWindowsLinux
macOS
Raspberry Pi
Windows
Linux
OS X
Solaris
Windows
IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64
Linux
macOS
Data schemeschema-freeschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesnoyesyesno
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.nono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLno infoVia inetgration in SQL ServerSQL-like query language (RQL)yesyesno
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC
Supported programming languagesC#.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C
C++
Java
Node.js
PL/SQL
Python
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyes infovia applicationsyesyes infoJavaPL/SQLno
Triggersyes infovia applicationsyesyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioningnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replicationMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesYes, via Full Spark Integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID, Cluster-wide transaction availableACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyesyesyes 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.yesyesyes infousing specific database classes
User concepts infoAccess controlno infoCan implement custom security layer via applicationsAuthorization levels configured per client per databaseAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standardno

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More resources
FatDBRavenDBSplice MachineTimesTenTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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