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DBMS > Badger vs. Hyprcubd vs. Solr vs. TerarkDB

System Properties Comparison Badger vs. Hyprcubd vs. Solr vs. TerarkDB

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonHyprcubd  Xexclude from comparisonSolr  Xexclude from comparisonTerarkDB  Xexclude from comparison
Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Serverless Time Series DBMSA widely used distributed, scalable search engine based on Apache LuceneA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelKey-value storeTime Series DBMSSearch engineKey-value store
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score42.91
Rank#24  Overall
#3  Search engines
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitegithub.com/­dgraph-io/­badgerhyprcubd.com (offline)solr.apache.orggithub.com/­bytedance/­terarkdb
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgersolr.apache.org/­resources.htmlbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperDGraph LabsHyprcubd, Inc.Apache Software FoundationByteDance, originally Terark
Initial release201720062016
Current release9.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache Version 2commercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoGoJavaC++
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsschema-free
Typing infopredefined data types such as float or datenoyes infotime, int, uint, float, stringyes infosupports customizable data types and automatic typingno
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.nonoyesno
Secondary indexesnonoyes infoAll search fields are automatically indexedno
SQL infoSupport of SQLnoSQL-like query languageSolr Parallel SQL Interfaceno
APIs and other access methodsgRPC (https)Java API
RESTful HTTP/JSON API
C++ API
Java API
Supported programming languagesGo.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C++
Java
Server-side scripts infoStored proceduresnonoJava pluginsno
Triggersnonoyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonooptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesnoyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlnotoken accessyesno

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More resources
BadgerHyprcubdSolrTerarkDB
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