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DBMS > Google Cloud Spanner vs. Memcached vs. Microsoft Azure Data Explorer vs. Stardog vs. TimesTen

System Properties Comparison Google Cloud Spanner vs. Memcached vs. Microsoft Azure Data Explorer vs. Stardog vs. TimesTen

Editorial information provided by DB-Engines
NameGoogle Cloud Spanner  Xexclude from comparisonMemcached  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonStardog  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.In-memory key-value store, originally intended for cachingFully managed big data interactive analytics platformEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualizationIn-Memory RDBMS compatible to Oracle
Primary database modelRelational DBMSKey-value 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score18.08
Rank#32  Overall
#4  Key-value stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score2.07
Rank#122  Overall
#11  Graph DBMS
#6  RDF stores
Score1.36
Rank#161  Overall
#75  Relational DBMS
Websitecloud.google.com/­spannerwww.memcached.orgazure.microsoft.com/­services/­data-explorerwww.stardog.comwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationcloud.google.com/­spanner/­docsgithub.com/­memcached/­memcached/­wikidocs.microsoft.com/­en-us/­azure/­data-explorerdocs.stardog.comdocs.oracle.com/­database/­timesten-18.1
DeveloperGoogleDanga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalMicrosoftStardog-UnionOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20172003201920101998
Current release1.6.27, May 2024cloud service with continuous releases7.3.0, May 202011 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourcecommercialOpen Source infoBSD licensecommercialcommercial 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 serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJava
Server operating systemshostedFreeBSD
Linux
OS X
Unix
Windows
hostedLinux
macOS
Windows
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeyesschema-freeFixed schema with schema-less datatypes (dynamic)schema-free and OWL/RDFS-schema supportyes
Typing infopredefined data types such as float or dateyesnoyes 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 possibleno
Secondary indexesyesnoall fields are automatically indexedyes infosupports real-time indexing in full-text and geospatialyes
SQL infoSupport of SQLyes infoQuery statements complying to ANSI 2011noKusto Query Language (KQL), SQL subsetYes, compatible with all major SQL variants through dedicated BI/SQL Serveryes
APIs and other access methodsgRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
Proprietary protocolMicrosoft 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
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresnonoYes, possible languages: KQL, Python, Ruser defined functions and aggregates, HTTP Server extensions in JavaPL/SQL
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infovia event handlersno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoImplicit feature of the cloud servicenonenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication with 3 replicas for regional instances.none infoRepcached, a Memcached patch, provides this functionallityyes 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 methodsyes infousing Google Cloud DataflownoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency in HA-ClusterImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynonoyes inforelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoStrict serializable isolationnonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesnoyesyesyes 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.nonoyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes infousing SASL (Simple Authentication and Security Layer) protocolAzure Active Directory AuthenticationAccess rights for users and rolesfine grained access rights according to SQL-standard

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More resources
Google Cloud SpannerMemcachedMicrosoft Azure Data ExplorerStardogTimesTen
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