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DBMS > Elasticsearch vs. Lovefield vs. Splice Machine vs. Tkrzw vs. Yaacomo

System Properties Comparison Elasticsearch vs. Lovefield vs. Splice Machine vs. Tkrzw vs. Yaacomo

Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonLovefield  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
DescriptionA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricEmbeddable relational database for web apps written in pure JavaScriptOpen-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 modelSearch engineRelational DBMSRelational DBMSKey-value storeRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score134.79
Rank#7  Overall
#1  Search engines
Score0.35
Rank#286  Overall
#131  Relational DBMS
Score0.54
Rank#257  Overall
#118  Relational DBMS
Score0.05
Rank#380  Overall
#59  Key-value stores
Websitewww.elastic.co/­elasticsearchgoogle.github.io/­lovefieldsplicemachine.comdbmx.net/­tkrzwyaacomo.com
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdsplicemachine.com/­how-it-works
DeveloperElasticGoogleSplice MachineMikio HirabayashiQ2WEB GmbH
Initial release20102014201420202009
Current release8.6, January 20232.1.12, February 20173.1, March 20210.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoElastic LicenseOpen Source infoApache 2.0Open 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 languageJavaJavaScriptJavaC++
Server operating systemsAll OS with a Java VMserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariLinux
OS X
Solaris
Windows
Linux
macOS
Android
Linux
Windows
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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 indexesyes infoAll search fields are automatically indexedyesyesyes
SQL infoSupport of SQLSQL-like query languageSQL-like query language infovia JavaScript builder patternyesnoyes
APIs and other access methodsJava API
RESTful HTTP/JSON API
JDBC
Native Spark Datasource
ODBC
JDBC
ODBC
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
JavaScriptC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyesnoyes infoJavano
Triggersyes infoby using the 'percolation' featureUsing read-only observersyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShared Nothhing Auto-Sharding, Columnar Partitioningnonehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneMulti-source replication
Source-replica replication
noneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop ConnectornoYes, via Full Spark Integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyes, 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.Memcached and Redis integrationyes infousing MemoryDByesyes infousing specific database classesyes
User concepts infoAccess controlnoAccess rights for users, groups and roles according to SQL-standardnofine grained access rights according to SQL-standard

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More resources
ElasticsearchLovefieldSplice MachineTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetYaacomo
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