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DBMS > Google Cloud Datastore vs. HEAVY.AI vs. Lovefield vs. Netezza vs. VictoriaMetrics

System Properties Comparison Google Cloud Datastore vs. HEAVY.AI vs. Lovefield vs. Netezza vs. VictoriaMetrics

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonLovefield  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareEmbeddable relational database for web apps written in pure JavaScriptData warehouse and analytics appliance part of IBM PureSystemsA fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelDocument storeRelational DBMSRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.29
Rank#293  Overall
#133  Relational DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score1.32
Rank#162  Overall
#14  Time Series DBMS
Websitecloud.google.com/­datastoregithub.com/­heavyai/­heavydb
www.heavy.ai
google.github.io/­lovefieldwww.ibm.com/­products/­netezzavictoriametrics.com
Technical documentationcloud.google.com/­datastore/­docsdocs.heavy.aigithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mddocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperGoogleHEAVY.AI, Inc.GoogleIBMVictoriaMetrics
Initial release20082016201420002018
Current release5.10, January 20222.1.12, February 2017v1.91, May 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; enterprise edition availableOpen Source infoApache 2.0commercialOpen 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 CUDAJavaScriptGo
Server operating systemshostedLinuxserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariLinux infoincluded in applianceFreeBSD
Linux
macOS
OpenBSD
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyes, details hereyesyesyes
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 indexesyesnoyesyes
SQL infoSupport of SQLSQL-like query language (GQL)yesSQL-like query language infovia JavaScript builder patternyesno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
Vega
JDBC
ODBC
OLE DB
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
JavaScriptC
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresusing Google App Enginenonoyesno
TriggersCallbacks using the Google Apps EnginenoUsing read-only observersnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoRound robinnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosMulti-source replicationnoneSource-replica replicationSynchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonoyesno
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 ConsistencyEventual 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 TransactionsnoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infousing MemoryDBno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardnoUsers with fine-grained authorization concept

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More resources
Google Cloud DatastoreHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022LovefieldNetezza infoAlso called PureData System for Analytics by IBMVictoriaMetrics
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