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DBMS > Lovefield vs. Pinecone vs. Tkrzw vs. Yaacomo

System Properties Comparison Lovefield vs. Pinecone vs. Tkrzw vs. Yaacomo

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Editorial information provided by DB-Engines
NameLovefield  Xexclude from comparisonPinecone  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 JavaScriptA managed, cloud-native vector databaseA 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 DBMSVector DBMSKey-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.33
Rank#286  Overall
#131  Relational DBMS
Score3.23
Rank#92  Overall
#3  Vector DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Websitegoogle.github.io/­lovefieldwww.pinecone.iodbmx.net/­tkrzwyaacomo.com
Technical documentationgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mddocs.pinecone.io/­docs/­overview
DeveloperGooglePinecone Systems, IncMikio HirabayashiQ2WEB GmbH
Initial release2014201920202009
Current release2.1.12, February 20170.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScriptC++
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafarihostedLinux
macOS
Android
Linux
Windows
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesString, Number, Booleannoyes
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.nononono
Secondary indexesyesyes
SQL infoSupport of SQLSQL-like query language infovia JavaScript builder patternnonoyes
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
Supported programming languagesJavaScriptPythonC++
Java
Python
Ruby
Server-side scripts infoStored proceduresnono
TriggersUsing read-only observersnoyes
Partitioning methods infoMethods for storing different data on different nodesnonenonehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infousing MemoryDBnoyes infousing specific database classesyes
User concepts infoAccess controlnonofine grained access rights according to SQL-standard

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More resources
LovefieldPineconeTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetYaacomo
DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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provided by Google News



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