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DBMS > Google Cloud Datastore vs. RDF4J vs. TDengine vs. TimescaleDB

System Properties Comparison Google Cloud Datastore vs. RDF4J vs. TDengine vs. TimescaleDB

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonTDengine  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Time Series DBMS and big data platformA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelDocument storeRDF storeTime Series DBMSTime Series DBMS
Secondary database modelsRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score0.69
Rank#230  Overall
#9  RDF stores
Score2.60
Rank#107  Overall
#8  Time Series DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitecloud.google.com/­datastorerdf4j.orggithub.com/­taosdata/­TDengine
tdengine.com
www.timescale.com
Technical documentationcloud.google.com/­datastore/­docsrdf4j.org/­documentationdocs.tdengine.comdocs.timescale.com
DeveloperGoogleSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.TDEngine, previously Taos DataTimescale
Initial release2008200420192017
Current release3.0, August 20222.15.0, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoAGPL V3, also commercial editions availableOpen Source infoApache 2.0
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.
Implementation languageJavaCC
Server operating systemshostedLinux
OS X
Unix
Windows
Linux
Windows
Linux
OS X
Windows
Data schemeschema-freeyes infoRDF Schemasyesyes
Typing infopredefined data types such as float or dateyes, details hereyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nonoyes
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like query language (GQL)noStandard SQL with extensions for time-series applicationsyes infofull PostgreSQL SQL syntax
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
JDBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
PHP
Python
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresusing Google App Engineyesnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
TriggersCallbacks using the Google Apps Engineyesyes, via alarm monitoringyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosnoneyesSource-replica replication with hot standby and reads on replicas info
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 Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoin-memory storage is supported as wellyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noyesfine grained access rights according to SQL-standard
More information provided by the system vendor
Google Cloud DatastoreRDF4J infoformerly known as SesameTDengineTimescaleDB
Specific characteristicsTDengineā„¢ 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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22 May 2024

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8 May 2024

TDengine 3.3.0.0 Release Notes
7 May 2024

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More resources
Google Cloud DatastoreRDF4J infoformerly known as SesameTDengineTimescaleDB
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