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

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

Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonStardog  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 platformEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualizationA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelSearch engineDocument storeRelational DBMS infocolumn orientedGraph DBMS
RDF store
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
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
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websiteaws.amazon.com/­cloudsearchcloud.google.com/­datastoreazure.microsoft.com/­services/­data-explorerwww.stardog.comwww.teradata.com
Technical documentationdocs.aws.amazon.com/­cloudsearchcloud.google.com/­datastore/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.stardog.comdocs.teradata.com
DeveloperAmazonGoogleMicrosoftStardog-UnionTeradata
Initial release20122008201920101984
Current releasecloud service with continuous releases7.3.0, May 2020Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/studentscommercial
Cloud-based only infoOnly available as a cloud serviceyesyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava
Server operating systemshostedhostedhostedLinux
macOS
Windows
hosted
Linux
Data schemeyesschema-freeFixed schema with schema-less datatypes (dynamic)schema-free and OWL/RDFS-schema supportyes
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.noyesno infoImport/export of XML data possibleyes
Secondary indexesyes infoall search fields are automatically indexedyesall fields are automatically indexedyes infosupports real-time indexing in full-text and geospatialyes 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, compatible with all major SQL variants through dedicated BI/SQL Serveryes 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
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
.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
Clojure
Groovy
Java
JavaScript
Python
Ruby
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 and aggregates, HTTP Server extensions in Javayes infoUDFs, stored procedures, table functions in parallel
TriggersnoCallbacks using the Google Apps Engineyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infovia event handlersyes
Partitioning methods infoMethods for storing different data on different nodesyes infoautomatic partitioning across Amazon Search Instance as requiredShardingSharding infoImplicit feature of the cloud servicenoneSharding 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.Multi-source replication in HA-ClusterMulti-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 Consistency in HA-ClusterImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyes inforelationships in graphsyes
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.nonoyesyes
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 AuthenticationAccess rights for users and rolesfine grained access rights according to SQL-standard

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More resources
Amazon CloudSearchGoogle Cloud DatastoreMicrosoft Azure Data ExplorerStardogTeradata
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