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DBMS > Amazon CloudSearch vs. Google Cloud Datastore vs. Microsoft Azure Data Explorer vs. PostgreSQL vs. Teradata

System Properties Comparison Amazon CloudSearch vs. Google Cloud Datastore vs. Microsoft Azure Data Explorer vs. PostgreSQL vs. Teradata

Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPostgreSQL  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionA hosted search engine service by Amazon with the data stored in Amazons cloudAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformFully managed big data interactive analytics platformWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelSearch engineDocument storeRelational 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 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
Document store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.85
Rank#137  Overall
#12  Search engines
Score4.47
Rank#76  Overall
#12  Document stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score645.54
Rank#4  Overall
#4  Relational DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websiteaws.amazon.com/­cloudsearchcloud.google.com/­datastoreazure.microsoft.com/­services/­data-explorerwww.postgresql.orgwww.teradata.com
Technical documentationdocs.aws.amazon.com/­cloudsearchcloud.google.com/­datastore/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerwww.postgresql.org/­docsdocs.teradata.com
DeveloperAmazonGoogleMicrosoftPostgreSQL Global Development Group infowww.postgresql.org/­developerTeradata
Initial release2012200820191989 info1989: Postgres, 1996: PostgreSQL1984
Current releasecloud service with continuous releases16.3, May 2024Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoBSDcommercial
Cloud-based only infoOnly available as a cloud serviceyesyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC
Server operating systemshostedhostedhostedFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
hosted
Linux
Data schemeyesschema-freeFixed schema with schema-less datatypes (dynamic)yesyes
Typing infopredefined data types such as float or dateyesyes, details hereyes 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.noyesyes infospecific XML-type available, but no XML query functionality.yes
Secondary indexesyes infoall search fields are automatically indexedyesall fields are automatically indexedyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLnoSQL-like query language (GQL)Kusto Query Language (KQL), SQL subsetyes infostandard with numerous extensionsyes infoSQL 2016 + extensions
APIs and other access methodsHTTP APIgRPC (using protocol buffers) 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
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
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++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresnousing Google App EngineYes, possible languages: KQL, Python, Ruser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yes infoUDFs, stored procedures, table functions in parallel
TriggersnoCallbacks using the Google Apps Engineyes 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 requiredShardingSharding infoImplicit feature of the cloud servicepartitioning by range, list and (since PostgreSQL 11) by hashSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesyes infomanaged transparently by AWSMulti-source replication using Paxosyes 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 methodsnoyes infousing Google Cloud DataflowSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDACID
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.nononoyes
User concepts infoAccess controlauthentication via encrypted signaturesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Azure Active Directory Authenticationfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Amazon CloudSearchGoogle Cloud DatastoreMicrosoft Azure Data ExplorerPostgreSQLTeradata
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