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DBMS > Google Cloud Datastore vs. Kinetica vs. NSDb vs. TimesTen

System Properties Comparison Google Cloud Datastore vs. Kinetica vs. NSDb vs. TimesTen

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonNSDb  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformFully vectorized database across both GPUs and CPUsScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesIn-Memory RDBMS compatible to Oracle
Primary database modelDocument storeRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.49
Rank#79  Overall
#12  Document stores
Score0.69
Rank#234  Overall
#107  Relational DBMS
Score0.00
Rank#396  Overall
#42  Time Series DBMS
Score1.35
Rank#165  Overall
#75  Relational DBMS
Websitecloud.google.com/­datastorewww.kinetica.comnsdb.iowww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationcloud.google.com/­datastore/­docsdocs.kinetica.comnsdb.io/­Architecturedocs.oracle.com/­database/­timesten-18.1
DeveloperGoogleKineticaOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release2008201220171998
Current release7.1, August 202111 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++Java, Scala
Server operating systemshostedLinuxLinux
macOS
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateyes, details hereyesyes: int, bigint, decimal, stringyes
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.nononono
Secondary indexesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like DML and DDL statementsSQL-like query languageyes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
gRPC
HTTP REST
WebSocket
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
Java
Scala
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresusing Google App Engineuser defined functionsnoPL/SQL
TriggersCallbacks using the Google Apps Engineyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSource-replica replicationMulti-source replication
Source-replica replication
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 configurationEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesUsing Apache Luceneyes infoby means of logfiles and checkpoints
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 and roles on table levelfine grained access rights according to SQL-standard

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More resources
Google Cloud DatastoreKineticaNSDbTimesTen
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