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DBMS > Google Cloud Datastore vs. Kinetica vs. Quasardb vs. TDengine

System Properties Comparison Google Cloud Datastore vs. Kinetica vs. Quasardb vs. TDengine

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonQuasardb  Xexclude from comparisonTDengine  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformFully vectorized database across both GPUs and CPUsDistributed, high-performance timeseries databaseTime Series DBMS and big data platform
Primary database modelDocument storeRelational DBMSTime Series DBMSTime Series DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.21
Rank#322  Overall
#29  Time Series DBMS
Score2.68
Rank#106  Overall
#9  Time Series DBMS
Websitecloud.google.com/­datastorewww.kinetica.comquasar.aigithub.com/­taosdata/­TDengine
tdengine.com
Technical documentationcloud.google.com/­datastore/­docsdocs.kinetica.comdoc.quasar.ai/­masterdocs.tdengine.com
DeveloperGoogleKineticaquasardbTDEngine, previously Taos Data
Initial release2008201220092019
Current release7.1, August 20213.14.1, January 20243.0, August 2022
License infoCommercial or Open Sourcecommercialcommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoAGPL V3, also commercial editions 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, C++C++C
Server operating systemshostedLinuxBSD
Linux
OS X
Windows
Linux
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyes, details hereyesyes infointeger and binaryyes
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 indexesyesyesyes infowith tagsno
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like DML and DDL statementsSQL-like query languageStandard SQL with extensions for time-series applications
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
HTTP APIJDBC
RESTful HTTP API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
Server-side scripts infoStored proceduresusing Google App Engineuser defined functionsnono
TriggersCallbacks using the Google Apps Engineyes infotriggers when inserted values for one or more columns fall within a specified rangenoyes, via alarm monitoring
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoconsistent hashingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSource-replica replicationSource-replica replication with selectable replication factoryes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownowith Hadoop 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 or Eventual Consistency depending on configurationImmediate Consistency
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
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using LevelDByes
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 infoTransient mode
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 levelCryptographically strong user authentication and audit trailyes
More information provided by the system vendor
Google Cloud DatastoreKineticaQuasardbTDengine
Specific characteristicsTDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
» more
Competitive advantagesHigh Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more
Typical application scenariosTDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more
Market metricsTDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more
Licensing and pricing modelsTDengine OSS is an open source, cloud native time series database. It includes built-in...
» more
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Google Cloud DatastoreKineticaQuasardbTDengine
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