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DBMS > Google Cloud Datastore vs. Kinetica vs. Microsoft Azure SQL Database vs. searchxml vs. XTDB

System Properties Comparison Google Cloud Datastore vs. Kinetica vs. Microsoft Azure SQL Database vs. searchxml vs. XTDB

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonsearchxml  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformFully vectorized database across both GPUs and CPUsDatabase as a Service offering with high compatibility to Microsoft SQL ServerDBMS for structured and unstructured content wrapped with an application serverA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelDocument storeRelational DBMSRelational DBMSNative XML DBMS
Search engine
Document store
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score0.00
Rank#383  Overall
#7  Native XML DBMS
#25  Search engines
Score0.11
Rank#343  Overall
#46  Document stores
Websitecloud.google.com/­datastorewww.kinetica.comazure.microsoft.com/­en-us/­products/­azure-sql/­databasewww.searchxml.net/­category/­productsgithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationcloud.google.com/­datastore/­docsdocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­azure-sqlwww.searchxml.net/­support/­handoutswww.xtdb.com/­docs
DeveloperGoogleKineticaMicrosoftinformationpartners gmbhJuxt Ltd.
Initial release20082012201020152019
Current release7.1, August 2021V121.01.19, September 2021
License infoCommercial or Open SourcecommercialcommercialcommercialcommercialOpen Source infoMIT License
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 languageC, C++C++C++Clojure
Server operating systemshostedLinuxhostedWindowsAll OS with a Java 8 (and higher) VM
Linux
Data schemeschema-freeyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyes, details hereyesyesyesyes, extensible-data-notation format
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.nonoyesyesno
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like DML and DDL statementsyesnolimited SQL, making use of Apache Calcite
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
RESTful HTTP API
WebDAV
XQuery
XSLT
HTTP REST
JDBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++ infomost other programming languages supported via APIsClojure
Java
Server-side scripts infoStored proceduresusing Google App Engineuser defined functionsTransact SQLyes infoon the application serverno
TriggersCallbacks using the Google Apps Engineyes infotriggers when inserted values for one or more columns fall within a specified rangeyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSource-replica replicationyes, with always 3 replicas availableyes infosychronisation to multiple collectionsyes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownononono
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.Immediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDmultiple readers, single writerACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAMno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles on table levelfine grained access rights according to SQL-standardDomain, group and role-based access control at the document level and for application services

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More resources
Google Cloud DatastoreKineticaMicrosoft Azure SQL Database infoformerly SQL AzuresearchxmlXTDB infoformerly named Crux
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