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DBMS > Google Cloud Bigtable vs. Google Cloud Datastore vs. TigerGraph vs. Tkrzw

System Properties Comparison Google Cloud Bigtable vs. Google Cloud Datastore vs. TigerGraph vs. Tkrzw

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonTigerGraph  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.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-timeA 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
Document storeGraph DBMSKey-value store
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
Score4.36
Rank#72  Overall
#12  Document stores
Score1.80
Rank#138  Overall
#13  Graph DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Websitecloud.google.com/­bigtablecloud.google.com/­datastorewww.tigergraph.comdbmx.net/­tkrzw
Technical documentationcloud.google.com/­bigtable/­docscloud.google.com/­datastore/­docsdocs.tigergraph.com
DeveloperGoogleGoogleMikio Hirabayashi
Initial release2015200820172020
Current release0.9.3, August 2020
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++
Server operating systemshostedhostedLinuxLinux
macOS
Data schemeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or datenoyes, details hereyesno
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 indexesnoyes
SQL infoSupport of SQLnoSQL-like query language (GQL)SQL-like query language (GSQL)no
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresnousing Google App Engineyesno
TriggersnoCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication using Paxosnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infousing Google Cloud Dataflowyesno
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 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 Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsyes infoRelationships in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
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.nononoyes infousing specific database classes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access controlno

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More resources
Google Cloud BigtableGoogle Cloud DatastoreTigerGraphTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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