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

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

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonTDengine  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 PlatformTime Series DBMS and big data platformA 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 storeTime Series DBMSKey-value store
Secondary database modelsRelational 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
Score4.36
Rank#72  Overall
#12  Document stores
Score2.68
Rank#106  Overall
#9  Time Series DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Websitecloud.google.com/­bigtablecloud.google.com/­datastoregithub.com/­taosdata/­TDengine
tdengine.com
dbmx.net/­tkrzw
Technical documentationcloud.google.com/­bigtable/­docscloud.google.com/­datastore/­docsdocs.tdengine.com
DeveloperGoogleGoogleTDEngine, previously Taos DataMikio Hirabayashi
Initial release2015200820192020
Current release3.0, August 20220.9.3, August 2020
License infoCommercial or Open SourcecommercialcommercialOpen Source infoAGPL V3, also commercial editions 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 languageCC++
Server operating systemshostedhostedLinux
Windows
Linux
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 indexesnoyesno
SQL infoSupport of SQLnoSQL-like query language (GQL)Standard SQL with extensions for time-series applicationsno
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
JDBC
RESTful HTTP API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresnousing Google App Enginenono
TriggersnoCallbacks using the Google Apps Engineyes, via alarm monitoringno
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 Paxosyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infousing Google Cloud Dataflowno
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 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 Transactions
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)yesno
More information provided by the system vendor
Google Cloud BigtableGoogle Cloud DatastoreTDengineTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
Specific characteristicsTDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
» more
Competitive advantagesHigh Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more
Typical application scenariosTDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more
Market metricsTDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more
Licensing and pricing modelsTDengine OSS is an open source, cloud native time series database. It includes built-in...
» more
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More resources
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