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DBMS > Google Cloud Datastore vs. HEAVY.AI vs. Rockset vs. Stardog

System Properties Comparison Google Cloud Datastore vs. HEAVY.AI vs. Rockset vs. Stardog

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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 comparisonRockset  Xexclude from comparisonStardog  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 hardwareA scalable, reliable search and analytics service in the cloud, built on RocksDBEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelDocument storeRelational DBMSDocument storeGraph DBMS
RDF store
Secondary database modelsSpatial DBMSRelational DBMS
Search engine
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
Score0.79
Rank#211  Overall
#35  Document stores
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websitecloud.google.com/­datastoregithub.com/­heavyai/­heavydb
www.heavy.ai
rockset.comwww.stardog.com
Technical documentationcloud.google.com/­datastore/­docsdocs.heavy.aidocs.rockset.comdocs.stardog.com
DeveloperGoogleHEAVY.AI, Inc.RocksetStardog-Union
Initial release2008201620192010
Current release5.10, January 20227.3.0, May 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; enterprise edition availablecommercialcommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ and CUDAC++Java
Server operating systemshostedLinuxhostedLinux
macOS
Windows
Data schemeschema-freeyesschema-freeschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyes, details hereyesdynamic typingyes
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.nonono infoingestion from XML files supportedno infoImport/export of XML data possible
Secondary indexesyesnoall fields are automatically indexedyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLSQL-like query language (GQL)yesRead-only SQL queries, including JOINsYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
Vega
HTTP RESTGraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
Go
Java
JavaScript (Node.js)
Python
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresusing Google App Enginenonouser defined functions and aggregates, HTTP Server extensions in Java
TriggersCallbacks using the Google Apps Enginenonoyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoRound robinAutomatic shardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosMulti-source replicationyesMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonono
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 ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnonoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
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-standardAccess rights for users and organizations can be defined via Rockset consoleAccess rights for users and roles

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More resources
Google Cloud DatastoreHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022RocksetStardog
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