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DBMS > DataFS vs. LevelDB vs. Splice Machine vs. Sqrrl vs. Tkrzw

System Properties Comparison DataFS vs. LevelDB vs. Splice Machine vs. Sqrrl vs. Tkrzw

Editorial information provided by DB-Engines
NameDataFS  Xexclude from comparisonLevelDB  Xexclude from comparisonSplice Machine  Xexclude from comparisonSqrrl  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionAll data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.Embeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkAdaptable, secure NoSQL built on Apache AccumuloA 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 modelObject oriented DBMSKey-value storeRelational DBMSDocument store
Graph DBMS
Key-value store
Wide column store
Key-value store
Secondary database modelsGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.06
Rank#354  Overall
#15  Object oriented DBMS
Score2.35
Rank#111  Overall
#19  Key-value stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitenewdatabase.comgithub.com/­google/­leveldbsplicemachine.comsqrrl.comdbmx.net/­tkrzw
Technical documentationdev.mobiland.com/­Overview.xspgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdsplicemachine.com/­how-it-works
DeveloperMobiland AGGoogleSplice MachineAmazon infooriginally Sqrrl Data, Inc.Mikio Hirabayashi
Initial release20182011201420122020
Current release1.1.263, October 20221.23, February 20213.1, March 20210.9.3, August 2020
License infoCommercial or Open SourcecommercialOpen Source infoBSDOpen 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

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Implementation languageC++JavaJavaC++
Server operating systemsWindowsIllumos
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
LinuxLinux
macOS
Data schemeClasses, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)schema-freeyesschema-freeschema-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.nonono
Secondary indexesnonoyesyes
SQL infoSupport of SQLnonoyesnono
APIs and other access methods.NET Client API
Proprietary client DLL
WinRT client
JDBC
Native Spark Datasource
ODBC
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languages.Net
C
C#
C++
VB.Net
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresnoyes infoJavanono
Triggersno, except callback-events from server when changes happenednoyesnono
Partitioning methods infoMethods for storing different data on different nodesProprietary Sharding systemnoneShared Nothhing Auto-Sharding, Columnar PartitioningSharding infomaking use of Hadoopnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
selectable replication factor infomaking use of Hadoopnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integrationyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.Immediate Consistency
Foreign keys infoReferential integrityyesnoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyes infowith automatic compression on writesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infousing specific database classes
User concepts infoAccess controlWindows-ProfilenoAccess rights for users, groups and roles according to SQL-standardCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)no

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DataFSLevelDBSplice MachineSqrrlTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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