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

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

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonCitus  Xexclude from comparisonEsgynDB  Xexclude from comparisonSphinx  Xexclude from comparisonVertica infoOpenText™ Vertica™  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 TrafodionOpen source search engine for searching in data from different sources, e.g. relational databasesCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelRelational DBMSRelational DBMSRelational DBMSSearch engineRelational DBMS infoColumn oriented
Secondary database modelsDocument storeDocument storeSpatial DBMS
Time Series DBMS
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
Score5.98
Rank#56  Overall
#5  Search engines
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websiteimpala.apache.orgwww.citusdata.comwww.esgyn.cnsphinxsearch.comwww.vertica.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.citusdata.comsphinxsearch.com/­docsvertica.com/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaEsgynSphinx Technologies Inc.OpenText infopreviously Micro Focus and Hewlett Packard
Initial release20132010201520012005
Current release4.1.0, June 20228.1, December 20183.5.1, February 202312.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoAGPL, commercial license also availablecommercialOpen Source infoGPL version 2, commercial licence availablecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CC++, JavaC++C++
Server operating systemsLinuxLinuxLinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
Data schemeyesyesyesyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesyesyesnoyes
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 indexesyesyesyesyes infofull-text index on all search fieldsNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infostandard, with numerous extensionsyesSQL-like query language (SphinxQL)Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
ODBC
Proprietary protocolADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
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.NetC++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
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 Proceduresnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyesnonoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedhorizontal partitioning, hierarchical partitioning
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 datacentersnoneMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyesnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.nononono
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-standardnofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Apache ImpalaCitusEsgynDBSphinxVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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Apache ImpalaCitusEsgynDBSphinxVertica infoOpenText™ Vertica™
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