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DBMS > Google Cloud Datastore vs. IRONdb vs. Kinetica vs. searchxml vs. Tkrzw

System Properties Comparison Google Cloud Datastore vs. IRONdb vs. Kinetica vs. searchxml vs. Tkrzw

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonIRONdb  Xexclude from comparisonKinetica  Xexclude from comparisonsearchxml  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityFully vectorized database across both GPUs and CPUsDBMS for structured and unstructured content wrapped with an application serverA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelDocument storeTime Series DBMSRelational DBMSNative XML DBMS
Search engine
Key-value store
Secondary database modelsSpatial 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
Score0.00
Rank#383  Overall
#7  Native XML DBMS
#25  Search engines
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitecloud.google.com/­datastorewww.circonus.com/solutions/time-series-database/www.kinetica.comwww.searchxml.net/­category/­productsdbmx.net/­tkrzw
Technical documentationcloud.google.com/­datastore/­docsdocs.circonus.com/irondb/category/getting-starteddocs.kinetica.comwww.searchxml.net/­support/­handouts
DeveloperGoogleCirconus LLC.Kineticainformationpartners gmbhMikio Hirabayashi
Initial release20082017201220152020
Current releaseV0.10.20, January 20187.1, August 20211.00.9.3, August 2020
License infoCommercial or Open SourcecommercialcommercialcommercialcommercialOpen Source infoApache Version 2.0
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 languageC and C++C, C++C++C++
Server operating systemshostedLinuxLinuxWindowsLinux
macOS
Data schemeschema-freeschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyes, details hereyes infotext, numeric, histogramsyesyesno
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.nononoyesno
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like DML and DDL statementsnono
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP APIJDBC
ODBC
RESTful HTTP API
RESTful HTTP API
WebDAV
XQuery
XSLT
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C++
Java
JavaScript (Node.js)
Python
C++ infomost other programming languages supported via APIsC++
Java
Python
Ruby
Server-side scripts infoStored proceduresusing Google App Engineyes, in Luauser defined functionsyes infoon the application serverno
TriggersCallbacks using the Google Apps Enginenoyes infotriggers when inserted values for one or more columns fall within a specified rangenono
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodeShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosconfigurable replication factor, datacenter awareSource-replica replicationyes infosychronisation to multiple collectionsnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownononono
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 per node, eventual consistency across nodesImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnonomultiple readers, single writer
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infoGPU vRAM or System RAMnoyes infousing specific database classes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noAccess rights for users and roles on table levelDomain, group and role-based access control at the document level and for application servicesno

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More resources
Google Cloud DatastoreIRONdbKineticasearchxmlTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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