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DBMS > Google Cloud Datastore vs. mSQL vs. OrigoDB vs. Splice Machine vs. VelocityDB

System Properties Comparison Google Cloud Datastore vs. mSQL vs. OrigoDB vs. Splice Machine vs. VelocityDB

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparisonOrigoDB  Xexclude from comparisonSplice Machine  Xexclude from comparisonVelocityDB  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformmSQL (Mini SQL) is a simple and lightweight RDBMSA fully ACID in-memory object graph databaseOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)
Primary database modelDocument storeRelational DBMSDocument store
Object oriented DBMS
Relational DBMSGraph DBMS
Object oriented DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score1.27
Rank#167  Overall
#77  Relational DBMS
Score0.00
Rank#383  Overall
#53  Document stores
#20  Object oriented DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score0.05
Rank#358  Overall
#36  Graph DBMS
#16  Object oriented DBMS
Websitecloud.google.com/­datastorehughestech.com.au/­products/­msqlorigodb.comsplicemachine.comvelocitydb.com
Technical documentationcloud.google.com/­datastore/­docsorigodb.com/­docssplicemachine.com/­how-it-worksvelocitydb.com/­UserGuide
DeveloperGoogleHughes TechnologiesRobert Friberg et alSplice MachineVelocityDB Inc
Initial release200819942009 infounder the name LiveDB20142011
Current release4.4, October 20213.1, March 20217.x
License infoCommercial or Open Sourcecommercialcommercial infofree licenses can be providedOpen SourceOpen Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC#JavaC#
Server operating systemshostedAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Linux
Windows
Linux
OS X
Solaris
Windows
Any that supports .NET
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or dateyes, details hereyesUser defined using .NET types and collectionsyesyes
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.nonono infocan be achieved using .NETno
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like query language (GQL)A subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggersnoyesno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
.NET Client API
HTTP API
LINQ
JDBC
Native Spark Datasource
ODBC
.Net
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Delphi
Java
Perl
PHP
Tcl
.NetC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
.Net
Server-side scripts infoStored proceduresusing Google App Enginenoyesyes infoJavano
TriggersCallbacks using the Google Apps Enginenoyes infoDomain EventsyesCallbacks are triggered when data changes
Partitioning methods infoMethods for storing different data on different nodesShardingnonehorizontal partitioning infoclient side managed; servers are not synchronizedShared Nothhing Auto-Sharding, Columnar PartitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosnoneSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud DataflownonoYes, via Full Spark Integrationno
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.noneImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnodepending on modelyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesnoyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyes infoWrite ahead logyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noRole based authorizationAccess rights for users, groups and roles according to SQL-standardBased on Windows Authentication

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More resources
Google Cloud DatastoremSQL infoMini SQLOrigoDBSplice MachineVelocityDB
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