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DBMS > Apache Phoenix vs. Elasticsearch vs. Microsoft Azure Data Explorer vs. PostgreSQL vs. TimesTen

System Properties Comparison Apache Phoenix vs. Elasticsearch vs. Microsoft Azure Data Explorer vs. PostgreSQL vs. TimesTen

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonElasticsearch  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPostgreSQL  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricFully managed big data interactive analytics platformWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLIn-Memory RDBMS compatible to Oracle
Primary database modelRelational DBMSSearch engineRelational DBMS infocolumn orientedRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Relational DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Document store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
Document store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score135.35
Rank#7  Overall
#1  Search engines
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score645.54
Rank#4  Overall
#4  Relational DBMS
Score1.31
Rank#163  Overall
#74  Relational DBMS
Websitephoenix.apache.orgwww.elastic.co/­elasticsearchazure.microsoft.com/­services/­data-explorerwww.postgresql.orgwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationphoenix.apache.orgwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.microsoft.com/­en-us/­azure/­data-explorerwww.postgresql.org/­docsdocs.oracle.com/­database/­timesten-18.1
DeveloperApache Software FoundationElasticMicrosoftPostgreSQL Global Development Group infowww.postgresql.org/­developerOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release2014201020191989 info1989: Postgres, 1996: PostgreSQL1998
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20198.6, January 2023cloud service with continuous releases16.3, May 202411 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoElastic LicensecommercialOpen Source infoBSDcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC
Server operating systemsLinux
Unix
Windows
All OS with a Java VMhostedFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-free infoFlexible type definitions. Once a type is defined, it is persistentFixed schema with schema-less datatypes (dynamic)yesyes
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyes
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.nonoyesyes infospecific XML-type available, but no XML query functionality.no
Secondary indexesyesyes infoAll search fields are automatically indexedall fields are automatically indexedyesyes
SQL infoSupport of SQLyesSQL-like query languageKusto Query Language (KQL), SQL subsetyes infostandard with numerous extensionsyes
APIs and other access methodsJDBCJava API
RESTful HTTP/JSON API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresuser defined functionsyesYes, possible languages: KQL, Python, Ruser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.PL/SQL
Triggersnoyes infoby using the 'percolation' featureyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud servicepartitioning by range, list and (since PostgreSQL 11) by hashnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication infoother methods possible by using 3rd party extensionsMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationES-Hadoop ConnectorSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesMemcached and Redis integrationnonoyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAzure Active Directory Authenticationfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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