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DBMS > Google Cloud Datastore vs. Kinetica vs. Microsoft Azure SQL Database vs. Spark SQL vs. Warp 10

System Properties Comparison Google Cloud Datastore vs. Kinetica vs. Microsoft Azure SQL Database vs. Spark SQL vs. Warp 10

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonSpark SQL  Xexclude from comparisonWarp 10  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 ServerSpark SQL is a component on top of 'Spark Core' for structured data processingTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelDocument storeRelational DBMSRelational DBMSRelational DBMSTime Series 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
Score4.47
Rank#76  Overall
#12  Document stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.07
Rank#349  Overall
#32  Time Series DBMS
Websitecloud.google.com/­datastorewww.kinetica.comazure.microsoft.com/­en-us/­products/­azure-sql/­databasespark.apache.org/­sqlwww.warp10.io
Technical documentationcloud.google.com/­datastore/­docsdocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­azure-sqlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.warp10.io/­content/­02_Getting_started
DeveloperGoogleKineticaMicrosoftApache Software FoundationSenX
Initial release20082012201020142015
Current release7.1, August 2021V123.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache 2.0Open Source infoApache License 2.0
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++ScalaJava
Server operating systemshostedLinuxhostedLinux
OS X
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyesyesschema-free
Typing infopredefined data types such as float or dateyes, details hereyesyesyesyes
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 indexesyesyesyesnono
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like DML and DDL statementsyesSQL-like DML and DDL statementsno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
JDBC
ODBC
HTTP API
Jupyter
WebSocket
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
Java
Python
R
Scala
Server-side scripts infoStored proceduresusing Google App Engineuser defined functionsTransact SQLnoyes infoWarpScript
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 nodesShardingShardingyes, utilizing Spark CoreSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSource-replica replicationyes, with always 3 replicas availablenoneselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonono
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 HBase
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 TransactionsnoACIDnono
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
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-standardnoMandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
Google Cloud DatastoreKineticaMicrosoft Azure SQL Database infoformerly SQL AzureSpark SQLWarp 10
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