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

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

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHypertable  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed 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.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformAn open source BigTable implementation based on distributed file systems such as HadoopA 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 storeWide column storeKey-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
Score0.07
Rank#372  Overall
#57  Key-value stores
Websitecloud.google.com/­bigtablecloud.google.com/­datastoredbmx.net/­tkrzw
Technical documentationcloud.google.com/­bigtable/­docscloud.google.com/­datastore/­docs
DeveloperGoogleGoogleHypertable Inc.Mikio Hirabayashi
Initial release2015200820092020
Current release0.9.8.11, March 20160.9.3, August 2020
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGNU version 3. Commercial license availableOpen 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 systemshostedhostedLinux
OS X
Windows infoan inofficial Windows port is available
Linux
macOS
Data schemeschema-freeschema-freeschema-freeschema-free
Typing infopredefined data types such as float or datenoyes, details herenono
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
Secondary indexesnoyesrestricted infoonly exact value or prefix value scans
SQL infoSupport of SQLnoSQL-like query language (GQL)nono
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
C++ API
Thrift
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
Perl
PHP
Python
Ruby
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresnousing Google App Enginenono
TriggersnoCallbacks using the Google Apps Enginenono
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 zonesMulti-source replication using Paxosselectable replication factor on file system levelnone
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
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.nonoyes 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)nono

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