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DBMS > LevelDB vs. Solr vs. Vitess vs. WakandaDB

System Properties Comparison LevelDB vs. Solr vs. Vitess vs. WakandaDB

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Editorial information provided by DB-Engines
NameLevelDB  Xexclude from comparisonSolr  Xexclude from comparisonVitess  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesA widely used distributed, scalable search engine based on Apache LuceneScalable, distributed, cloud-native DBMS, extending MySQLWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelKey-value storeSearch engineRelational DBMSObject oriented DBMS
Secondary database modelsSpatial DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.35
Rank#111  Overall
#19  Key-value stores
Score42.91
Rank#24  Overall
#3  Search engines
Score0.82
Rank#209  Overall
#97  Relational DBMS
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websitegithub.com/­google/­leveldbsolr.apache.orgvitess.iowakanda.github.io
Technical documentationgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdsolr.apache.org/­resources.htmlvitess.io/­docswakanda.github.io/­doc
DeveloperGoogleApache Software FoundationThe Linux Foundation, PlanetScaleWakanda SAS
Initial release2011200620132012
Current release1.23, February 20219.6.0, April 202415.0.2, December 20222.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourceOpen Source infoBSDOpen Source infoApache Version 2Open Source infoApache Version 2.0, commercial licenses availableOpen Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaGoC++, JavaScript
Server operating systemsIllumos
Linux
OS X
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Docker
Linux
macOS
Linux
OS X
Windows
Data schemeschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyesyes
Typing infopredefined data types such as float or datenoyes infosupports customizable data types and automatic typingyesyes
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.noyesno
Secondary indexesnoyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLnoSolr Parallel SQL Interfaceyes infowith proprietary extensionsno
APIs and other access methodsJava API
RESTful HTTP/JSON API
ADO.NET
JDBC
MySQL protocol
ODBC
RESTful HTTP API
Supported programming languagesC++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
JavaScript
Server-side scripts infoStored proceduresnoJava pluginsyes infoproprietary syntaxyes
Triggersnoyes infoUser configurable commands triggered on index changesyesyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Immediate Consistency
Foreign keys infoReferential integritynonoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingACID at shard levelACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engineyes
Durability infoSupport for making data persistentyes infowith automatic compression on writesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlnoyesUsers with fine-grained authorization concept infono user groups or rolesyes

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LevelDBSolrVitessWakandaDB
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