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DBMS > Google Cloud Datastore vs. Hive vs. Netezza vs. Prometheus vs. Quasardb

System Properties Comparison Google Cloud Datastore vs. Hive vs. Netezza vs. Prometheus vs. Quasardb

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHive  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonPrometheus  Xexclude from comparisonQuasardb  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platformdata warehouse software for querying and managing large distributed datasets, built on HadoopData warehouse and analytics appliance part of IBM PureSystemsOpen-source Time Series DBMS and monitoring systemDistributed, high-performance timeseries database
Primary database modelDocument storeRelational DBMSRelational DBMSTime Series DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Websitecloud.google.com/­datastorehive.apache.orgwww.ibm.com/­products/­netezzaprometheus.ioquasar.ai
Technical documentationcloud.google.com/­datastore/­docscwiki.apache.org/­confluence/­display/­Hive/­Homeprometheus.io/­docsdoc.quasar.ai/­master
DeveloperGoogleApache Software Foundation infoinitially developed by FacebookIBMquasardb
Initial release20082012200020152009
Current release3.1.3, April 20223.14.1, January 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialOpen Source infoApache 2.0commercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
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 languageJavaGoC++
Server operating systemshostedAll OS with a Java VMLinux infoincluded in applianceLinux
Windows
BSD
Linux
OS X
Windows
Data schemeschema-freeyesyesyesschema-free
Typing infopredefined data types such as float or dateyes, details hereyesyesNumeric data onlyyes infointeger and binary
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.nono infoImport of XML data possibleno
Secondary indexesyesyesyesnoyes infowith tags
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like DML and DDL statementsyesnoSQL-like query language
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
JDBC
ODBC
OLE DB
RESTful HTTP/JSON APIHTTP API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
PHP
Python
C
C++
Fortran
Java
Lua
Perl
Python
R
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresusing Google App Engineyes infouser defined functions and integration of map-reduceyesnono
TriggersCallbacks using the Google Apps Enginenononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingShardingSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosselectable replication factorSource-replica replicationyes infoby FederationSource-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyes infoquery execution via MapReduceyesnowith 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.Eventual ConsistencynoneImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes 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, groups and rolesUsers with fine-grained authorization conceptnoCryptographically strong user authentication and audit trail

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More resources
Google Cloud DatastoreHiveNetezza infoAlso called PureData System for Analytics by IBMPrometheusQuasardb
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