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DBMS > Google Cloud Datastore vs. Kinetica vs. Microsoft Azure SQL Database vs. OpenTSDB vs. Sadas Engine

System Properties Comparison Google Cloud Datastore vs. Kinetica vs. Microsoft Azure SQL Database vs. OpenTSDB vs. Sadas Engine

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonOpenTSDB  Xexclude from comparisonSadas Engine  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 ServerScalable Time Series DBMS based on HBaseSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments
Primary database modelDocument storeRelational DBMSRelational DBMSTime Series DBMSRelational DBMS
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
Score4.36
Rank#72  Overall
#12  Document stores
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score76.78
Rank#16  Overall
#11  Relational DBMS
Score1.68
Rank#142  Overall
#12  Time Series DBMS
Score0.07
Rank#373  Overall
#157  Relational DBMS
Websitecloud.google.com/­datastorewww.kinetica.comazure.microsoft.com/­en-us/­products/­azure-sql/­databaseopentsdb.netwww.sadasengine.com
Technical documentationcloud.google.com/­datastore/­docsdocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­azure-sqlopentsdb.net/­docs/­build/­html/­index.htmlwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
DeveloperGoogleKineticaMicrosoftcurrently maintained by Yahoo and other contributorsSADAS s.r.l.
Initial release20082012201020112006
Current release7.1, August 2021V128.0
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoLGPLcommercial infofree trial version available
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++JavaC++
Server operating systemshostedLinuxhostedLinux
Windows
AIX
Linux
Windows
Data schemeschema-freeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyes, details hereyesyesnumeric data for metrics, strings for tagsyes
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.nonoyesnono
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like DML and DDL statementsyesnoyes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
HTTP API
Telnet API
JDBC
ODBC
Proprietary protocol
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
Erlang
Go
Java
Python
R
Ruby
.Net
C
C#
C++
Groovy
Java
PHP
Python
Server-side scripts infoStored proceduresusing Google App Engineuser defined functionsTransact SQLnono
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 nodesShardingShardingSharding infobased on HBasehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSource-replica replicationyes, with always 3 replicas availableselectable replication factor infobased on HBasenone
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 infobased on HBaseImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDno
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 RAMnoyes infomanaged by 'Learn by Usage'
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-standardnoAccess rights for users, groups and roles according to SQL-standard

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More resources
Google Cloud DatastoreKineticaMicrosoft Azure SQL Database infoformerly SQL AzureOpenTSDBSadas Engine
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