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DBMS > Apache Impala vs. Apache Phoenix vs. CouchDB vs. Solr vs. Splice Machine

System Properties Comparison Apache Impala vs. Apache Phoenix vs. CouchDB vs. Solr vs. Splice Machine

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonApache Phoenix  Xexclude from comparisonCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonSolr  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA scale-out RDBMS with evolutionary schema built on Apache HBaseA native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.A widely used distributed, scalable search engine based on Apache LuceneOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSRelational DBMSDocument storeSearch engineRelational DBMS
Secondary database modelsDocument storeSpatial DBMS infousing the Geocouch extensionSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score9.30
Rank#45  Overall
#7  Document stores
Score42.91
Rank#24  Overall
#3  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteimpala.apache.orgphoenix.apache.orgcouchdb.apache.orgsolr.apache.orgsplicemachine.com
Technical documentationimpala.apache.org/­impala-docs.htmlphoenix.apache.orgdocs.couchdb.org/­en/­stablesolr.apache.org/­resources.htmlsplicemachine.com/­how-it-works
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software FoundationApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerApache Software FoundationSplice Machine
Initial release20132014200520062014
Current release4.1.0, June 20225.0-HBase2, July 2018 and 4.15-HBase1, December 20193.3.3, December 20239.6.0, April 20243.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoApache version 2Open Source infoApache Version 2Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaErlangJavaJava
Server operating systemsLinuxLinux
Unix
Windows
Android
BSD
Linux
OS X
Solaris
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Solaris
Windows
Data schemeyesyes infolate-bound, schema-on-read capabilitiesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyesnoyes infosupports customizable data types and automatic typingyes
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.nononoyes
Secondary indexesyesyesyes infovia viewsyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesnoSolr Parallel SQL Interfaceyes
APIs and other access methodsJDBC
ODBC
JDBCRESTful HTTP/JSON APIJava API
RESTful HTTP/JSON API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functionsView functions in JavaScriptJava pluginsyes infoJava
Triggersnonoyesyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoimproved architecture with release 2.0ShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
yesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceHadoop integrationyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual ConsistencyEventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno infoatomic operations within a single document possibleoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infostrategy: optimistic lockingyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights for users can be defined per databaseyesAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache ImpalaApache PhoenixCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"SolrSplice Machine
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