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DBMS > Amazon CloudSearch vs. Kdb vs. Microsoft Azure Data Explorer vs. PostgreSQL vs. Tibero

System Properties Comparison Amazon CloudSearch vs. Kdb vs. Microsoft Azure Data Explorer vs. PostgreSQL vs. Tibero

Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonKdb  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPostgreSQL  Xexclude from comparisonTibero  Xexclude from comparison
DescriptionA hosted search engine service by Amazon with the data stored in Amazons cloudHigh performance Time Series DBMSFully managed big data interactive analytics platformWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLA secure RDBMS, designed for easy portability from Oracle
Primary database modelSearch engineTime Series DBMS
Vector DBMS
Relational 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 modelsRelational DBMSDocument 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
Score1.81
Rank#137  Overall
#12  Search engines
Score7.71
Rank#49  Overall
#2  Time Series DBMS
#1  Vector DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score636.25
Rank#4  Overall
#4  Relational DBMS
Score1.59
Rank#148  Overall
#68  Relational DBMS
Websiteaws.amazon.com/­cloudsearchkx.comazure.microsoft.com/­services/­data-explorerwww.postgresql.orgus.tmaxsoft.com/­products/­tibero
Technical documentationdocs.aws.amazon.com/­cloudsearchcode.kx.comdocs.microsoft.com/­en-us/­azure/­data-explorerwww.postgresql.org/­docstechnet.tmaxsoft.com/­upload/­download/­online/­tibero/­pver-20150504-000002/­index.html
DeveloperAmazonKx Systems, a division of First Derivatives plcMicrosoftPostgreSQL Global Development Group infowww.postgresql.org/­developerTmaxSoft
Initial release20122000 infokdb was released 2000, kdb+ in 200320191989 info1989: Postgres, 1996: PostgreSQL2003
Current release3.6, May 2018cloud service with continuous releases16.3, May 20246, April 2015
License infoCommercial or Open Sourcecommercialcommercial infofree 32-bit versioncommercialOpen Source infoBSDcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageqCC and Assembler
Server operating systemshostedLinux
OS X
Solaris
Windows
hostedFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
AIX
HP-UX
Linux
Solaris
Windows
Data schemeyesyesFixed 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.yesyesyes infospecific XML-type available, but no XML query functionality.yes
Secondary indexesyes infoall search fields are automatically indexedyes infotable attribute 'grouped'all fields are automatically indexedyesyes
SQL infoSupport of SQLnoSQL-like query language (q)Kusto Query Language (KQL), SQL subsetyes infostandard with numerous extensionsyes
APIs and other access methodsHTTP APIHTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
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)
Tibero CLI
Supported programming languagesC
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic
Server-side scripts infoStored proceduresnouser defined functionsYes, possible languages: KQL, Python, Ruser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.Persistent Stored Procedure (PSM)
Triggersnoyes infowith viewsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesyes
Partitioning methods infoMethods for storing different data on different nodesyes infoautomatic partitioning across Amazon Search Instance as requiredhorizontal partitioningSharding infoImplicit feature of the cloud servicepartitioning by range, list and (since PostgreSQL 11) by hashhorizontal partitioning infoby range, hash, list or composite
Replication methods infoMethods for redundantly storing data on multiple nodesyes infomanaged transparently by AWSSource-replica replicationyes 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 methodsnono infosimilar paradigm used for internal processingSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACIDACID
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.yesnonono infoplanned for next version
User concepts infoAccess controlauthentication via encrypted signaturesrights management via user accountsAzure Active Directory Authenticationfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard (SQL 92, SQL 99)
More information provided by the system vendor
Amazon CloudSearchKdbMicrosoft Azure Data ExplorerPostgreSQLTibero
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
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Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
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Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
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More resources
Amazon CloudSearchKdbMicrosoft Azure Data ExplorerPostgreSQLTibero
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