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DBMS > Apache Impala vs. Apache Phoenix vs. eXtremeDB vs. Hive vs. Vertica

System Properties Comparison Apache Impala vs. Apache Phoenix vs. eXtremeDB vs. Hive vs. Vertica

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonApache Phoenix  Xexclude from comparisoneXtremeDB  Xexclude from comparisonHive  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA scale-out RDBMS with evolutionary schema built on Apache HBaseNatively in-memory DBMS with options for persistency, high-availability and clusteringdata warehouse software for querying and managing large distributed datasets, built on HadoopCloud 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 DBMS
Time Series DBMS
Relational DBMSRelational DBMS infoColumn oriented
Secondary database modelsDocument 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
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.74
Rank#223  Overall
#103  Relational DBMS
#18  Time Series DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websiteimpala.apache.orgphoenix.apache.orgwww.mcobject.comhive.apache.orgwww.vertica.com
Technical documentationimpala.apache.org/­impala-docs.htmlphoenix.apache.orgwww.mcobject.com/­docs/­extremedb.htmcwiki.apache.org/­confluence/­display/­Hive/­Homevertica.com/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software FoundationMcObjectApache Software Foundation infoinitially developed by FacebookOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20132014200120122005
Current release4.1.0, June 20225.0-HBase2, July 2018 and 4.15-HBase1, December 20198.2, 20213.1.3, April 202212.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0commercialOpen Source infoApache Version 2commercial 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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC and C++JavaC++
Server operating systemsLinuxLinux
Unix
Windows
AIX
HP-UX
Linux
macOS
Solaris
Windows
All OS with a Java VMLinux
Data schemeyesyes infolate-bound, schema-on-read capabilitiesyesyesYes, 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 dateyesyesyesyesyes
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.nonono infosupport of XML interfaces availableno
Secondary indexesyesyesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyes infowith the option: eXtremeSQLSQL-like DML and DDL statementsFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
ODBC
JDBC.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
JDBC
ODBC
Thrift
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
C
C#
C++
Java
Lua
Python
Scala
C++
Java
PHP
Python
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 functionsyesyes infouser defined functions and integration of map-reduceyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnonoyes infoby defining eventsnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning / shardingShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication
Source-replica replication
Active Replication Fabric™ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
selectable replication factorMulti-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 MapReduceHadoop integrationnoyes infoquery execution via MapReduceno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyes
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.noyesyesno
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, groups and rolesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Apache ImpalaApache PhoenixeXtremeDBHiveVertica infoOpenText™ Vertica™
Specific characteristicseXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
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Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
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Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
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Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
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Cost-based models and subscription-based models are both available. One license is...
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More resources
Apache ImpalaApache PhoenixeXtremeDBHiveVertica infoOpenText™ Vertica™
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