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DBMS > Apache Impala vs. Citus vs. EsgynDB vs. OrientDB vs. Sphinx

System Properties Comparison Apache Impala vs. Citus vs. EsgynDB vs. OrientDB vs. Sphinx

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonCitus  Xexclude from comparisonEsgynDB  Xexclude from comparisonOrientDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionMulti-model DBMS (Document, Graph, Key/Value)Open source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSRelational DBMSRelational DBMSDocument store
Graph DBMS
Key-value store
Search engine
Secondary database modelsDocument storeDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score3.19
Rank#93  Overall
#16  Document stores
#7  Graph DBMS
#14  Key-value stores
Score5.98
Rank#56  Overall
#5  Search engines
Websiteimpala.apache.orgwww.citusdata.comwww.esgyn.cnorientdb.orgsphinxsearch.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.citusdata.comwww.orientdb.com/­docs/­last/­index.htmlsphinxsearch.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaEsgynOrientDB LTD; CallidusCloud; SAPSphinx Technologies Inc.
Initial release20132010201520102001
Current release4.1.0, June 20228.1, December 20183.2.29, March 20243.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoAGPL, commercial license also availablecommercialOpen Source infoApache version 2Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CC++, JavaJavaC++
Server operating systemsLinuxLinuxLinuxAll OS with a Java JDK (>= JDK 6)FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesyesschema-free infoSchema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")yes
Typing infopredefined data types such as float or dateyesyesyesyesno
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.noyes infospecific XML type available, but no XML query functionalitynono
Secondary indexesyesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infostandard, with numerous extensionsyesSQL-like query language, no joinsSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
ODBC
Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API
Proprietary protocol
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
All languages supporting JDBC/ODBC/ADO.Net.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
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 functions and integration of map-reduceuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.Java Stored ProceduresJava, Javascriptno
TriggersnoyesnoHooksno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replication infoother methods possible by using 3rd party extensionsMulti-source replication between multi datacentersMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyesno infocould be achieved with distributed queriesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesyes inforelationship in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes 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.nonono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardAccess rights for users and roles; record level security configurableno

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More resources
Apache ImpalaCitusEsgynDBOrientDBSphinx
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