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DBMS > Google Cloud Bigtable vs. GridGain vs. Stardog vs. Tkrzw

System Properties Comparison Google Cloud Bigtable vs. GridGain vs. Stardog vs. Tkrzw

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonGridGain  Xexclude from comparisonStardog  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  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.GridGain is an in-memory computing platform, built on Apache IgniteEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualizationA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelKey-value store
Wide column store
Columnar
Key-value store
Object oriented DBMS
Relational DBMS
Graph DBMS
RDF store
Key-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Score1.48
Rank#150  Overall
#1  Columnar
#26  Key-value stores
#2  Object oriented DBMS
#69  Relational DBMS
Score1.93
Rank#121  Overall
#10  Graph DBMS
#6  RDF stores
Score0.00
Rank#385  Overall
#61  Key-value stores
Websitecloud.google.com/­bigtablewww.gridgain.comwww.stardog.comdbmx.net/­tkrzw
Technical documentationcloud.google.com/­bigtable/­docswww.gridgain.com/­docs/­index.htmldocs.stardog.com
DeveloperGoogleGridGain Systems, Inc.Stardog-UnionMikio Hirabayashi
Initial release2015200720102020
Current releaseGridGain 8.5.17.3.0, May 20200.9.3, August 2020
License infoCommercial or Open Sourcecommercialcommercial, open sourcecommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/studentsOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .Net, Python, REST, SQLJavaC++
Server operating systemshostedLinux
OS X
Solaris
Windows
z/OS
Linux
macOS
Windows
Linux
macOS
Data schemeschema-freeyesschema-free and OWL/RDFS-schema supportschema-free
Typing infopredefined data types such as float or datenoyesyesno
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.noyesno infoImport/export of XML data possibleno
Secondary indexesnoyesyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLnoANSI-99 for query and DML statements, subset of DDLYes, compatible with all major SQL variants through dedicated BI/SQL Serverno
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
GraphQL 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#
C++
Java
PHP
Python
Ruby
Scala
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)user defined functions and aggregates, HTTP Server extensions in Javano
Triggersnoyes (cache interceptors and events)yes infovia event handlersno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyes (replicated cache)Multi-source replication in HA-Clusternone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency in HA-ClusterImmediate Consistency
Foreign keys infoReferential integritynonoyes inforelationships in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACIDACID
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.noyesyesyes infousing specific database classes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access control
Security Hooks for custom implementations
Access rights for users and rolesno

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More resources
Google Cloud BigtableGridGainStardogTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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