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DBMS > Apache Impala vs. Apache Phoenix vs. Greenplum vs. JaguarDB vs. Microsoft Azure Table Storage

System Properties Comparison Apache Impala vs. Apache Phoenix vs. Greenplum vs. JaguarDB vs. Microsoft Azure Table Storage

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonApache Phoenix  Xexclude from comparisonGreenplum  Xexclude from comparisonJaguarDB  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA scale-out RDBMS with evolutionary schema built on Apache HBaseAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.Performant, highly scalable DBMS for AI and IoT applicationsA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelRelational DBMSRelational DBMSRelational DBMSKey-value store
Vector DBMS
Wide column store
Secondary database modelsDocument storeDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score1.90
Rank#125  Overall
#59  Relational DBMS
Score7.71
Rank#46  Overall
#29  Relational DBMS
Score0.00
Rank#385  Overall
#61  Key-value stores
#16  Vector DBMS
Score3.55
Rank#80  Overall
#6  Wide column stores
Websiteimpala.apache.orgphoenix.apache.orggreenplum.orgwww.jaguardb.comazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationimpala.apache.org/­impala-docs.htmlphoenix.apache.orgdocs.greenplum.orgwww.jaguardb.com/­support.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software FoundationPivotal Software Inc.DataJaguar, Inc.Microsoft
Initial release20132014200520152012
Current release4.1.0, June 20225.0-HBase2, July 2018 and 4.15-HBase1, December 20197.0.0, September 20233.3 July 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoGPL V3.0commercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC++ infothe server part. Clients available in other languages
Server operating systemsLinuxLinux
Unix
Windows
LinuxLinuxhosted
Data schemeyesyes infolate-bound, schema-on-read capabilitiesyesyesschema-free
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.nonoyes infosince Version 4.2nono
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyesA subset of ANSI SQL is implemented infobut no views, foreign keys, triggersno
APIs and other access methodsJDBC
ODBC
JDBCJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C
Java
Perl
Python
R
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functionsyesnono
Triggersnonoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication
Source-replica replication
Source-replica replicationMulti-source replicationyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceHadoop integrationyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDnooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.noyesnonono
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-tenancyfine grained access rights according to SQL-standardrights management via user accountsAccess rights based on private key authentication or shared access signatures

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More resources
Apache ImpalaApache PhoenixGreenplumJaguarDBMicrosoft Azure Table Storage
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