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DBMS > Apache Pinot vs. Neo4j vs. Solr vs. Sphinx

System Properties Comparison Apache Pinot vs. Neo4j vs. Solr vs. Sphinx

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonNeo4j  Xexclude from comparisonSolr  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyScalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offeringsA widely used distributed, scalable search engine based on Apache LuceneOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSGraph DBMSSearch engineSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.38
Rank#275  Overall
#126  Relational DBMS
Score44.89
Rank#21  Overall
#1  Graph DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Score5.95
Rank#55  Overall
#5  Search engines
Websitepinot.apache.orgneo4j.comsolr.apache.orgsphinxsearch.com
Technical documentationdocs.pinot.apache.orgneo4j.com/­docssolr.apache.org/­resources.htmlsphinxsearch.com/­docs
DeveloperApache Software Foundation and contributorsNeo4j, Inc.Apache Software FoundationSphinx Technologies Inc.
Initial release2015200720062001
Current release1.0.0, September 20235.20, May 20249.6.1, May 20243.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGPL version3, commercial licenses availableOpen Source infoApache Version 2Open Source infoGPL version 2, commercial licence 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.
Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.
Implementation languageJavaJava, ScalaJavaC++
Server operating systemsAll OS with a Java JDK11 or higherLinux infoCan also be used server-less as embedded Java database.
OS X
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
Data schemeyesschema-free and schema-optionalyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyesyes 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.yes
Secondary indexesyes infopluggable indexing subsystem, by default Apache Luceneyes infoAll search fields are automatically indexedyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query languagenoSolr Parallel SQL InterfaceSQL-like query language (SphinxQL)
APIs and other access methodsJDBCBolt protocol
Cypher query language
Java API
Neo4j-OGM infoObject Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3
Java API
RESTful HTTP/JSON API
Proprietary protocol
Supported programming languagesGo
Java
Python
.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
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
Server-side scripts infoStored proceduresyes infoUser defined Procedures and FunctionsJava pluginsno
Triggersyes infovia event handleryes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningyes using Neo4j FabricShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesCausal Clustering using Raft protocol infoavailable in in Enterprise Version onlyyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemCausal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode
Eventual Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDoptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes
User concepts infoAccess controlUsers, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)yesno
More information provided by the system vendor
Apache PinotNeo4jSolrSphinx
Specific characteristicsNeo4j delivers graph technology that has been battle tested for performance and scale...
» more
Competitive advantagesNeo4j is the market leader, graph database category creator, and the most widely...
» more
Typical application scenariosReal-Time Recommendations Master Data Management Identity and Access Management Network...
» more
Key customersOver 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
» more
Market metricsNeo4j boasts the world's largest graph database ecosystem with more than 140 million...
» more
Licensing and pricing modelsGPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
» more
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