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DBMS > Google Cloud Datastore vs. GridDB vs. Prometheus vs. Splice Machine

System Properties Comparison Google Cloud Datastore vs. GridDB vs. Prometheus vs. Splice Machine

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonGridDB  Xexclude from comparisonPrometheus  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformScalable in-memory time series database optimized for IoT and Big DataOpen-source Time Series DBMS and monitoring systemOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument storeTime Series DBMSTime Series DBMSRelational DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitecloud.google.com/­datastoregriddb.netprometheus.iosplicemachine.com
Technical documentationcloud.google.com/­datastore/­docsdocs.griddb.netprometheus.io/­docssplicemachine.com/­how-it-works
DeveloperGoogleToshiba CorporationSplice Machine
Initial release2008201320152014
Current release5.1, August 20223.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache 2.0Open Source infoAGPL 3.0, commercial license available
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++GoJava
Server operating systemshostedLinuxLinux
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyes, details hereyes infonumerical, string, blob, geometry, boolean, timestampNumeric data onlyyes
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 infoImport of XML data possible
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like query language (GQL)SQL92, SQL-like TQL (Toshiba Query Language)noyes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
RESTful HTTP/JSON APIJDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresusing Google App Enginenonoyes infoJava
TriggersCallbacks using the Google Apps Engineyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSource-replica replicationyes infoby FederationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud DataflowConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnoYes, via Full Spark Integration
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 within container, eventual consistency across containersnoneImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID at container levelnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users can be defined per databasenoAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
Google Cloud DatastoreGridDBPrometheusSplice Machine
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
Google Cloud DatastoreGridDBPrometheusSplice Machine
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