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DBMS > Google Cloud Datastore vs. Kinetica vs. RavenDB vs. RRDtool

System Properties Comparison Google Cloud Datastore vs. Kinetica vs. RavenDB vs. RRDtool

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonRavenDB  Xexclude from comparisonRRDtool  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformFully vectorized database across both GPUs and CPUsOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseIndustry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database. infoThe data is stored in a circular buffer, thus the system storage footprint remains constant over time.
Primary database modelDocument storeRelational DBMSDocument storeTime Series DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Graph DBMS
Spatial DBMS
Time Series 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
Score2.92
Rank#101  Overall
#18  Document stores
Score1.87
Rank#136  Overall
#11  Time Series DBMS
Websitecloud.google.com/­datastorewww.kinetica.comravendb.netoss.oetiker.ch/­rrdtool
Technical documentationcloud.google.com/­datastore/­docsdocs.kinetica.comravendb.net/­docsoss.oetiker.ch/­rrdtool/­doc
DeveloperGoogleKineticaHibernating RhinosTobias Oetiker
Initial release2008201220101999
Current release7.1, August 20215.4, July 20221.8.0, 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoAGPL version 3, commercial license availableOpen Source infoGPL V2 and FLOSS
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++C#C infoImplementations in Java (e.g. RRD4J) and C# available
Server operating systemshostedLinuxLinux
macOS
Raspberry Pi
Windows
HP-UX
Linux
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyes, details hereyesnoNumeric data only
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 infoExporting into and restoring from XML files possible
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like DML and DDL statementsSQL-like query language (RQL)no
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
in-process shared library
Pipes
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C infowith librrd library
C# infowith a different implementation of RRDTool
Java infowith a different implementation of RRDTool
JavaScript (Node.js) infowith a different implementation of RRDTool
Lua
Perl
PHP infowith a wrapper library
Python
Ruby
Server-side scripts infoStored proceduresusing Google App Engineuser defined functionsyesno
TriggersCallbacks using the Google Apps Engineyes infotriggers when inserted values for one or more columns fall within a specified rangeyesno
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 replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownoyesno
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 configurationDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.none
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID, Cluster-wide transaction availableno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoby using the rrdcached daemon
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.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 levelAuthorization levels configured per client per databaseno

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More resources
Google Cloud DatastoreKineticaRavenDBRRDtool
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