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

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

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonQuasardb  Xexclude from comparisonTimescaleDB  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 databaseA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
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
Score4.13
Rank#71  Overall
#12  Document stores
Score0.42
Rank#261  Overall
#120  Relational DBMS
Score0.13
Rank#332  Overall
#28  Time Series DBMS
Score4.06
Rank#73  Overall
#5  Time Series DBMS
Websitecloud.google.com/­datastorewww.kinetica.comquasar.aiwww.timescale.com
Technical documentationcloud.google.com/­datastore/­docsdocs.kinetica.comdoc.quasar.ai/­masterdocs.timescale.com
DeveloperGoogleKineticaquasardbTimescale
Initial release2008201220092017
Current release7.1, August 20213.14.1, January 20242.15.0, May 2024
License infoCommercial or Open Sourcecommercialcommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoApache 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 languageC, C++C++C
Server operating systemshostedLinuxBSD
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyes, details hereyesyes infointeger and binarynumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nononoyes
Secondary indexesyesyesyes infowith tagsyes
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like DML and DDL statementsSQL-like query languageyes infofull PostgreSQL SQL syntax
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
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
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresusing Google App Engineuser defined functionsnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
TriggersCallbacks using the Google Apps Engineyes infotriggers when inserted values for one or more columns fall within a specified rangenoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoconsistent hashingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSource-replica replicationSource-replica replication with selectable replication factorSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownowith Hadoop integrationno
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDACID
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 modeno
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 trailfine grained access rights according to SQL-standard

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More resources
Google Cloud DatastoreKineticaQuasardbTimescaleDB
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