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

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

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonKinetica  Xexclude from comparisonStardog  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
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 CPUsEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualizationTransactional SQL-on-Hadoop DBMS
Primary database modelKey-value store
Wide column store
Relational DBMSGraph DBMS
RDF store
Relational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websitecloud.google.com/­bigtablewww.kinetica.comwww.stardog.comtrafodion.apache.org
Technical documentationcloud.google.com/­bigtable/­docsdocs.kinetica.comdocs.stardog.comtrafodion.apache.org/­documentation.html
DeveloperGoogleKineticaStardog-UnionApache Software Foundation, originally developed by HP
Initial release2015201220102014
Current release7.1, August 20217.3.0, May 20202.3.0, February 2019
License infoCommercial or Open Sourcecommercialcommercialcommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/studentsOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++JavaC++, Java
Server operating systemshostedLinuxLinux
macOS
Windows
Linux
Data schemeschema-freeyesschema-free and OWL/RDFS-schema supportyes
Typing infopredefined data types such as float or datenoyesyesyes
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 infoImport/export of XML data possibleno
Secondary indexesnoyesyes infosupports real-time indexing in full-text and geospatialyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsYes, compatible with all major SQL variants through dedicated BI/SQL Serveryes
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
RESTful HTTP API
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
ADO.NET
JDBC
ODBC
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
JavaScript (Node.js)
Python
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresnouser defined functionsuser defined functions and aggregates, HTTP Server extensions in JavaJava Stored Procedures
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infovia event handlersno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationMulti-source replication in HA-Clusteryes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonoyes infovia user defined functions and HBase
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-ClusterImmediate Consistency
Foreign keys infoReferential integritynoyesyes inforelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnoACIDACID
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 RAMyesno
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 levelAccess rights for users and rolesfine grained access rights according to SQL-standard

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More resources
Google Cloud BigtableKineticaStardogTrafodion
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