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DBMS > Apache IoTDB vs. Graph Engine vs. H2 vs. TimescaleDB vs. YDB

System Properties Comparison Apache IoTDB vs. Graph Engine vs. H2 vs. TimescaleDB vs. YDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonH2  Xexclude from comparisonTimescaleDB  Xexclude from comparisonYDB  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 FlinkA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineFull-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLA distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API
Primary database modelTime Series DBMSGraph DBMS
Key-value store
Relational DBMSTime Series DBMSDocument store
Relational DBMS
Secondary database modelsSpatial DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score8.13
Rank#49  Overall
#31  Relational DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Score0.35
Rank#278  Overall
#43  Document stores
#127  Relational DBMS
Websiteiotdb.apache.orgwww.graphengine.iowww.h2database.comwww.timescale.comgithub.com/­ydb-platform/­ydb
ydb.tech
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.graphengine.io/­docs/­manualwww.h2database.com/­html/­main.htmldocs.timescale.comydb.tech/­en/­docs
DeveloperApache Software FoundationMicrosoftThomas MuellerTimescaleYandex
Initial release20182010200520172019
Current release1.1.0, April 20232.2.220, July 20232.13.0, November 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoMIT LicenseOpen Source infodual-licence (Mozilla public license, Eclipse public license)Open Source infoApache 2.0Open Source infoApache 2.0; commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava.NET and CJavaC
Server operating systemsAll OS with a Java VM (>= 1.8).NETAll OS with a Java VMLinux
OS X
Windows
Linux
Data schemeyesyesyesyesFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyesyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyes
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.nononoyesno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query languagenoyesyes infofull PostgreSQL SQL syntaxSQL-like query language (YQL)
APIs and other access methodsJDBC
Native API
RESTful HTTP APIJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
RESTful HTTP API (DynamoDB compatible)
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
C++
F#
Visual Basic
Java.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Go
Java
JavaScript (Node.js)
PHP
Python
Server-side scripts infoStored proceduresyesyesJava Stored Procedures and User-Defined Functionsuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellno
Triggersyesnoyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal partitioningnoneyes, across time and space (hash partitioning) attributesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasWith clustering: 2 database servers on different computers operate on identical copies of a databaseSource-replica replication with hot standby and reads on replicas infoActive-passive shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesnono
User concepts infoAccess controlyesfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardAccess rights defined for Yandex Cloud users

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More resources
Apache IoTDBGraph Engine infoformer name: TrinityH2TimescaleDBYDB
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