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DBMS > Google Cloud Datastore vs. MySQL vs. TDengine vs. Teradata

System Properties Comparison Google Cloud Datastore vs. MySQL vs. TDengine vs. Teradata

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonMySQL  Xexclude from comparisonTDengine  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformWidely used open source RDBMSTime Series DBMS and big data platformA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelDocument storeRelational DBMS infoKey/Value like access via memcached APITime Series DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Relational DBMSDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.49
Rank#79  Overall
#12  Document stores
Score1087.72
Rank#2  Overall
#2  Relational DBMS
Score2.68
Rank#109  Overall
#8  Time Series DBMS
Score47.84
Rank#21  Overall
#15  Relational DBMS
Websitecloud.google.com/­datastorewww.mysql.comgithub.com/­taosdata/­TDengine
tdengine.com
www.teradata.com
Technical documentationcloud.google.com/­datastore/­docsdev.mysql.com/­docdocs.tdengine.comdocs.teradata.com
DeveloperGoogleOracle infosince 2010, originally MySQL AB, then SunTDEngine, previously Taos DataTeradata
Initial release2008199520191984
Current release8.3.0, January 20243.0, August 2022Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourcecommercialOpen Source infoGPL version 2. Commercial licenses with extended functionallity are availableOpen Source infoGPL V3, also commercial editions availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.
Implementation languageC and C++C
Server operating systemshostedFreeBSD
Linux
OS X
Solaris
Windows
Linux
Windows
hosted
Linux
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyes, details hereyesyesyes
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.noyesnoyes
Secondary indexesyesyesnoyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLSQL-like query language (GQL)yes infowith proprietary extensionsStandard SQL with extensions for time-series applicationsyes infoSQL 2016 + extensions
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
Proprietary native API
JDBC
RESTful HTTP API
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresusing Google App Engineyes infoproprietary syntaxnoyes infoUDFs, stored procedures, table functions in parallel
TriggersCallbacks using the Google Apps Engineyesyes, via alarm monitoringyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning, sharding with MySQL Cluster or MySQL FabricShardingSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosMulti-source replication
Source-replica replication
yesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 integrityyes infovia ReferenceProperties or Ancestor pathsyes infonot for MyISAM storage enginenoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infonot for MyISAM storage engineACID
Concurrency infoSupport for concurrent manipulation of datayesyes infotable locks or row locks depending on storage engineyesyes
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.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users with fine-grained authorization concept infono user groups or rolesyesfine grained access rights according to SQL-standard
More information provided by the system vendor
Google Cloud DatastoreMySQLTDengineTeradata
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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