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

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

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonGridGain  Xexclude from comparisonKinetica  Xexclude from comparisonNSDb  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformGridGain is an in-memory computing platform, built on Apache IgniteFully vectorized database across both GPUs and CPUsScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes
Primary database modelDocument storeKey-value store
Relational DBMS
Relational DBMSTime Series DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.08
Rank#369  Overall
#40  Time Series DBMS
Websitecloud.google.com/­datastorewww.gridgain.comwww.kinetica.comnsdb.io
Technical documentationcloud.google.com/­datastore/­docswww.gridgain.com/­docs/­index.htmldocs.kinetica.comnsdb.io/­Architecture
DeveloperGoogleGridGain Systems, Inc.Kinetica
Initial release2008200720122017
Current releaseGridGain 8.5.17.1, August 2021
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache Version 2.0
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 languageJava, C++, .NetC, C++Java, Scala
Server operating systemshostedLinux
OS X
Solaris
Windows
LinuxLinux
macOS
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateyes, details hereyesyesyes: int, bigint, decimal, string
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.noyesnono
Secondary indexesyesyesyesall fields are automatically indexed
SQL infoSupport of SQLSQL-like query language (GQL)ANSI-99 for query and DML statements, subset of DDLSQL-like DML and DDL statementsSQL-like query language
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
RESTful HTTP API
gRPC
HTTP REST
WebSocket
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
Java
Scala
Server-side scripts infoStored proceduresusing Google App Engineyes (compute grid and cache interceptors can be used instead)user defined functionsno
TriggersCallbacks using the Google Apps Engineyes (cache interceptors and events)yes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes (replicated cache)Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyes (compute grid and hadoop accelerator)nono
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 ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesUsing Apache Lucene
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementationsAccess rights for users and roles on table level

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More resources
Google Cloud DatastoreGridGainKineticaNSDb
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