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DBMS > Google Cloud Datastore vs. Hive vs. Kinetica vs. Microsoft Azure SQL Database vs. TerarkDB

System Properties Comparison Google Cloud Datastore vs. Hive vs. Kinetica vs. Microsoft Azure SQL Database vs. TerarkDB

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHive  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonTerarkDB  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platformdata warehouse software for querying and managing large distributed datasets, built on HadoopFully vectorized database across both GPUs and CPUsDatabase as a Service offering with high compatibility to Microsoft SQL ServerA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelDocument storeRelational DBMSRelational DBMSRelational DBMSKey-value 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
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitecloud.google.com/­datastorehive.apache.orgwww.kinetica.comazure.microsoft.com/­en-us/­products/­azure-sql/­databasegithub.com/­bytedance/­terarkdb
Technical documentationcloud.google.com/­datastore/­docscwiki.apache.org/­confluence/­display/­Hive/­Homedocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­azure-sqlbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperGoogleApache Software Foundation infoinitially developed by FacebookKineticaMicrosoftByteDance, originally Terark
Initial release20082012201220102016
Current release3.1.3, April 20227.1, August 2021V12
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialcommercialcommercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, C++C++C++
Server operating systemshostedAll OS with a Java VMLinuxhosted
Data schemeschema-freeyesyesyesschema-free
Typing infopredefined data types such as float or dateyes, details hereyesyesyesno
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.nonoyesno
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like DML and DDL statementsSQL-like DML and DDL statementsyesno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
C++ API
Java API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
PHP
Python
C++
Java
JavaScript (Node.js)
Python
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
Server-side scripts infoStored proceduresusing Google App Engineyes infouser defined functions and integration of map-reduceuser defined functionsTransact SQLno
TriggersCallbacks using the Google Apps Enginenoyes infotriggers when inserted values for one or more columns fall within a specified rangeyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosselectable replication factorSource-replica replicationyes, with always 3 replicas availablenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyes infoquery execution via MapReducenonono
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 ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnonoACIDno
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.noyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and rolesAccess rights for users and roles on table levelfine grained access rights according to SQL-standardno

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More resources
Google Cloud DatastoreHiveKineticaMicrosoft Azure SQL Database infoformerly SQL AzureTerarkDB
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