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DBMS > Lovefield vs. Oracle Berkeley DB vs. Splice Machine vs. Tkrzw vs. Yaacomo

System Properties Comparison Lovefield vs. Oracle Berkeley DB vs. Splice Machine vs. Tkrzw vs. Yaacomo

Editorial information provided by DB-Engines
NameLovefield  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSplice Machine  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionEmbeddable relational database for web apps written in pure JavaScriptWidely used in-process key-value storeOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto CabinetOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSKey-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.32
Rank#290  Overall
#132  Relational DBMS
Score2.52
Rank#114  Overall
#20  Key-value stores
#3  Native XML DBMS
Score0.54
Rank#255  Overall
#116  Relational DBMS
Score0.09
Rank#354  Overall
#51  Key-value stores
Websitegoogle.github.io/­lovefieldwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlsplicemachine.comdbmx.net/­tkrzwyaacomo.com
Technical documentationgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mddocs.oracle.com/­cd/­E17076_05/­html/­index.htmlsplicemachine.com/­how-it-works
DeveloperGoogleOracle infooriginally developed by Sleepycat, which was acquired by OracleSplice MachineMikio HirabayashiQ2WEB GmbH
Initial release20141994201420202009
Current release2.1.12, February 201718.1.40, May 20203.1, March 20210.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infocommercial license availableOpen Source infoAGPL 3.0, commercial license availableOpen Source infoApache Version 2.0commercial
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 languageJavaScriptC, Java, C++ (depending on the Berkeley DB edition)JavaC++
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Solaris
Windows
Linux
macOS
Android
Linux
Windows
Data schemeyesschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesnoyesnoyes
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.noyes infoonly with the Berkeley DB XML editionnono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query language infovia JavaScript builder patternyes infoSQL interfaced based on SQLite is availableyesnoyes
APIs and other access methodsJDBC
Native Spark Datasource
ODBC
JDBC
ODBC
Supported programming languagesJavaScript.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresnonoyes infoJavano
TriggersUsing read-only observersyes infoonly for the SQL APIyesnoyes
Partitioning methods infoMethods for storing different data on different nodesnonenoneShared Nothhing Auto-Sharding, Columnar Partitioningnonehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationMulti-source replication
Source-replica replication
noneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infousing MemoryDByesyesyes infousing specific database classesyes
User concepts infoAccess controlnonoAccess rights for users, groups and roles according to SQL-standardnofine grained access rights according to SQL-standard

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More resources
LovefieldOracle Berkeley DBSplice MachineTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetYaacomo
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