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DBMS > EDB Postgres vs. Google Cloud Datastore vs. Microsoft Azure Data Explorer vs. SAP SQL Anywhere vs. Teradata

System Properties Comparison EDB Postgres vs. Google Cloud Datastore vs. Microsoft Azure Data Explorer vs. SAP SQL Anywhere vs. Teradata

Editorial information provided by DB-Engines
NameEDB Postgres  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSAP SQL Anywhere infoformerly called Adaptive Server Anywhere  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionThe EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformFully managed big data interactive analytics platformRDBMS database and synchronization technologies for server, desktop, remote office, and mobile environmentsA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelRelational DBMSDocument storeRelational DBMS infocolumn orientedRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial 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
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.90
Rank#135  Overall
#63  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score4.25
Rank#79  Overall
#43  Relational DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websitewww.enterprisedb.comcloud.google.com/­datastoreazure.microsoft.com/­services/­data-explorerwww.sap.com/­products/­technology-platform/­sql-anywhere.htmlwww.teradata.com
Technical documentationwww.enterprisedb.com/­docscloud.google.com/­datastore/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerhelp.sap.com/­docs/­SAP_SQL_Anywheredocs.teradata.com
DeveloperEnterpriseDBGoogleMicrosoftSAP infoformerly SybaseTeradata
Initial release20052008201919921984
Current release14, December 2021cloud service with continuous releases17, July 2015Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open Sourcecommercial infoBSD for PostgreSQL-componentscommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC
Server operating systemsLinux
Windows
hostedhostedAIX
HP-UX
Linux
OS X
Solaris
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.yes infospecific XML-type available, but no XML query functionality.noyesyesyes
Secondary indexesyesyesall fields are automatically indexedyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLyes infostandard with numerous extensionsSQL-like query language (GQL)Kusto Query Language (KQL), SQL subsetyesyes infoSQL 2016 + extensions
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
HTTP API
JDBC
ODBC
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languages.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.using Google App EngineYes, possible languages: KQL, Python, Ryes, in C/C++, Java, .Net or Perlyes infoUDFs, stored procedures, table functions in parallel
TriggersyesCallbacks using the Google Apps Engineyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning infoby hash, list or rangeShardingSharding infoImplicit feature of the cloud servicenoneSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationMulti-source replication using Paxosyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication infoDatabase mirroringMulti-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 ConsistencyImmediate 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 integrityyesyes infovia ReferenceProperties or Ancestor pathsnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyesyes
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.nononoyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess 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
EDB PostgresGoogle Cloud DatastoreMicrosoft Azure Data ExplorerSAP SQL Anywhere infoformerly called Adaptive Server AnywhereTeradata
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