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

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

Editorial information provided by DB-Engines
NameLovefield  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonPlanetScale  Xexclude from comparisonSplice Machine  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 storeScalable, distributed, serverless MySQL database platform built on top of VitessOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkOpenCL 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 DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.33
Rank#286  Overall
#131  Relational DBMS
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Score1.49
Rank#155  Overall
#72  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitegoogle.github.io/­lovefieldwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlplanetscale.comsplicemachine.comyaacomo.com
Technical documentationgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mddocs.oracle.com/­cd/­E17076_05/­html/­index.htmlplanetscale.com/­docssplicemachine.com/­how-it-works
DeveloperGoogleOracle infooriginally developed by Sleepycat, which was acquired by OraclePlanetScaleSplice MachineQ2WEB GmbH
Initial release20141994202020142009
Current release2.1.12, February 201718.1.40, May 20203.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infocommercial license availablecommercialOpen Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScriptC, Java, C++ (depending on the Berkeley DB edition)GoJava
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
Docker
Linux
macOS
Linux
OS X
Solaris
Windows
Android
Linux
Windows
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesnoyesyesyes
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 editionno
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like query language infovia JavaScript builder patternyes infoSQL interfaced based on SQLite is availableyes infowith proprietary extensionsyesyes
APIs and other access methodsADO.NET
JDBC
MySQL protocol
ODBC
JDBC
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
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonoyes infoproprietary syntaxyes infoJava
TriggersUsing read-only observersyes infoonly for the SQL APIyesyesyes
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardingShared Nothhing Auto-Sharding, Columnar Partitioninghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency across shards
Immediate Consistency within a shard
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyes infonot for MyISAM storage engineyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID at shard levelACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes infotable locks or row locks depending on storage engineyes, multi-version concurrency control (MVCC)yes
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 MemoryDByesyesyesyes
User concepts infoAccess controlnonoUsers with fine-grained authorization concept infono user groups or rolesAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard

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More resources
LovefieldOracle Berkeley DBPlanetScaleSplice MachineYaacomo
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