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DBMS > Google Cloud Datastore vs. Prometheus vs. TDSQL for MySQL

System Properties Comparison Google Cloud Datastore vs. Prometheus vs. TDSQL for MySQL

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonPrometheus  Xexclude from comparisonTDSQL for MySQL  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformOpen-source Time Series DBMS and monitoring systemA high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.
Primary database modelDocument storeTime Series DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Score0.85
Rank#205  Overall
#95  Relational DBMS
Websitecloud.google.com/­datastoreprometheus.iowww.tencentcloud.com/­products/­dcdb
Technical documentationcloud.google.com/­datastore/­docsprometheus.io/­docswww.tencentcloud.com/­document/­product/­1042
DeveloperGoogleTencent
Initial release200820152013
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGo
Server operating systemshostedLinux
Windows
hosted
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateyes, details hereNumeric data onlyyes
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.nono infoImport of XML data possibleno
Secondary indexesyesnoyes
SQL infoSupport of SQLSQL-like query language (GQL)noyes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP/JSON APIJDBC
ODBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
C
C#
C++
Java
PHP
Python
Ruby
Server-side scripts infoStored proceduresusing Google App Enginenoyes
TriggersCallbacks using the Google Apps Enginenoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes infoby FederationMulti-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.noneImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noUsers with fine-grained authorization concept

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More resources
Google Cloud DatastorePrometheusTDSQL for MySQL
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