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DBMS > Google Cloud Bigtable vs. Kinetica vs. openGemini vs. Stardog

System Properties Comparison Google Cloud Bigtable vs. Kinetica vs. openGemini vs. Stardog

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonKinetica  Xexclude from comparisonopenGemini  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Fully vectorized database across both GPUs and CPUsAn open source distributed Time Series DBMS with high concurrency, high performance, and high scalabilityEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelKey-value store
Wide column store
Relational DBMSTime Series DBMSGraph DBMS
RDF store
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.09
Rank#361  Overall
#37  Time Series DBMS
Score2.07
Rank#122  Overall
#11  Graph DBMS
#6  RDF stores
Websitecloud.google.com/­bigtablewww.kinetica.comwww.opengemini.org
github.com/­openGemini
www.stardog.com
Technical documentationcloud.google.com/­bigtable/­docsdocs.kinetica.comdocs.opengemini.org/­guidedocs.stardog.com
DeveloperGoogleKineticaHuawei and openGemini communityStardog-Union
Initial release2015201220222010
Current release7.1, August 20211.1, July 20237.3.0, May 2020
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0commercial 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 serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++GoJava
Server operating systemshostedLinuxLinux
Windows
Linux
macOS
Windows
Data schemeschema-freeyesschema-freeschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or datenoyesInteger, Float, Boolean, Stringyes
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 infoImport/export of XML data possible
Secondary indexesnoyesyesyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLnoSQL-like DML and DDL statementsSQL-like query languageYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
RESTful HTTP API
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 languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
JavaScript (Node.js)
Python
C
C++
Go
Java
JavaScript (Node.js)
Python
Rust
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresnouser defined functionsnouser defined functions and aggregates, HTTP Server extensions in Java
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangenoyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationyesMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency or Eventual Consistency depending on configurationImmediate Consistency in HA-Cluster
Foreign keys infoReferential integritynoyesnoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnonoACID
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.noyes infoGPU vRAM or System RAMyesyes
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 levelAdministrators and common users accountsAccess rights for users and roles

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More resources
Google Cloud BigtableKineticaopenGeminiStardog
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