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DBMS > Solr vs. Sphinx vs. Splice Machine vs. Teradata

System Properties Comparison Solr vs. Sphinx vs. Splice Machine vs. Teradata

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Editorial information provided by DB-Engines
NameSolr  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionA 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 SparkA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelSearch engineSearch engineRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMSDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score42.91
Rank#24  Overall
#3  Search engines
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websitesolr.apache.orgsphinxsearch.comsplicemachine.comwww.teradata.com
Technical documentationsolr.apache.org/­resources.htmlsphinxsearch.com/­docssplicemachine.com/­how-it-worksdocs.teradata.com
DeveloperApache Software FoundationSphinx Technologies Inc.Splice MachineTeradata
Initial release2006200120141984
Current release9.5.0, February 20243.5.1, February 20233.1, March 2021Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++Java
Server operating systemsAll 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
hosted
Linux
Data schemeyes infoDynamic Fields enables on-the-fly addition of new fieldsyesyesyes
Typing infopredefined data types such as float or dateyes infosupports customizable data types and automatic typingnoyesyes
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.yesyes
Secondary indexesyes infoAll search fields are automatically indexedyes infofull-text index on all search fieldsyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLSolr Parallel SQL InterfaceSQL-like query language (SphinxQL)yesyes infoSQL 2016 + extensions
APIs and other access methodsJava API
RESTful HTTP/JSON API
Proprietary protocolJDBC
Native Spark Datasource
ODBC
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languages.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
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresJava pluginsnoyes infoJavayes infoUDFs, stored procedures, table functions in parallel
Triggersyes infoUser configurable commands triggered on index changesnoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar PartitioningSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reducenoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataoptimistic lockingnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyes infoThe original contents of fields are not stored in the Sphinx index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlyesnoAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard

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SolrSphinxSplice MachineTeradata
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