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DBMS > Badger vs. GigaSpaces vs. Solr vs. Sphinx vs. Splice Machine

System Properties Comparison Badger vs. GigaSpaces vs. Solr vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonGigaSpaces  Xexclude from comparisonSolr  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsA widely used distributed, scalable search engine based on Apache LuceneOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value storeDocument store
Object oriented DBMS infoValues are user defined objects
Search engineSearch engineRelational DBMS
Secondary database modelsGraph DBMS
Search engine
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#320  Overall
#47  Key-value stores
Score1.03
Rank#188  Overall
#32  Document stores
#6  Object oriented DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Score5.95
Rank#55  Overall
#5  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerwww.gigaspaces.comsolr.apache.orgsphinxsearch.comsplicemachine.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.gigaspaces.com/­latest/­landing.htmlsolr.apache.org/­resources.htmlsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperDGraph LabsGigaspaces TechnologiesApache Software FoundationSphinx Technologies Inc.Splice Machine
Initial release20172000200620012014
Current release15.5, September 20209.6.1, May 20243.5.1, February 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2; Commercial licenses availableOpen Source infoApache Version 2Open Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
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 languageGoJava, C++, .NetJavaC++Java
Server operating systemsBSD
Linux
OS X
Solaris
Windows
Linux
macOS
Solaris
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyesyes
Typing infopredefined data types such as float or datenoyesyes infosupports customizable data types and automatic typingnoyes
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.nono infoXML can be used for describing objects metadatayes
Secondary indexesnoyesyes infoAll search fields are automatically indexedyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoSQL-99 for query and DML statementsSolr Parallel SQL InterfaceSQL-like query language (SphinxQL)yes
APIs and other access methodsGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
Java API
RESTful HTTP/JSON API
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesGo.Net
C++
Java
Python
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyesJava pluginsnoyes infoJava
Triggersnoyes, event driven architectureyes infoUser configurable commands triggered on index changesnoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
yesnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoMap-Reduce pattern can be built with XAP task executorsspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reducenoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDoptimistic lockingnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes
User concepts infoAccess controlnoRole-based access controlyesnoAccess rights for users, groups and roles according to SQL-standard

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BadgerGigaSpacesSolrSphinxSplice Machine
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