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DBMS > Apache IoTDB vs. Dgraph vs. Google Cloud Datastore vs. openGauss vs. TimescaleDB

System Properties Comparison Apache IoTDB vs. Dgraph vs. Google Cloud Datastore vs. openGauss vs. TimescaleDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDgraph  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonopenGauss  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkDistributed and scalable native Graph DBMSAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformAn enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by HuaweiA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelTime Series DBMSGraph DBMSDocument storeRelational DBMSTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score1.45
Rank#156  Overall
#15  Graph DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score1.08
Rank#183  Overall
#84  Relational DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websiteiotdb.apache.orgdgraph.iocloud.google.com/­datastoregitee.com/­opengauss
opengauss.org
www.timescale.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldgraph.io/­docscloud.google.com/­datastore/­docsdocs.opengauss.org/­en
gitee.com/­opengauss/­docs
docs.timescale.com
DeveloperApache Software FoundationDgraph Labs, Inc.GoogleHuawei and openGauss communityTimescale
Initial release20182016200820192017
Current release1.1.0, April 20233.0, March 20222.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0commercialOpen SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoC, C++, JavaC
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Windows
hostedLinuxLinux
OS X
Windows
Data schemeyesschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes, details hereyesnumerics, 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.nonononoyes
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like query languagenoSQL-like query language (GQL)ANSI SQL 2011yes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
Native API
GraphQL query language
gRPC (using protocol buffers) API
HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Java
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyesnousing Google App Engineyesuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
TriggersyesnoCallbacks using the Google Apps Engineyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)yesShardinghorizontal partitioning (by range, list and hash)yes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasSynchronous replication via RaftMulti-source replication using PaxosSource-replica replicationSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate 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 integritynonoyes infovia ReferenceProperties or Ancestor pathsyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonono
User concepts infoAccess controlyesno infoPlanned for future releasesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Apache IoTDBDgraphGoogle Cloud DatastoreopenGaussTimescaleDB
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