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DBMS > Apache IoTDB vs. Databend vs. H2 vs. JSqlDb vs. TimescaleDB

System Properties Comparison Apache IoTDB vs. Databend vs. H2 vs. JSqlDb vs. TimescaleDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDatabend  Xexclude from comparisonH2  Xexclude from comparisonJSqlDb  Xexclude from comparisonTimescaleDB  Xexclude from comparison
JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.
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 FlinkAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityFull-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.JavaScript Query Language Database, stores JavaScript objects and primitivesA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelTime Series DBMSRelational DBMSRelational DBMSDocument store
Object oriented DBMS
Time Series 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
Score0.30
Rank#287  Overall
#130  Relational DBMS
Score8.13
Rank#49  Overall
#31  Relational DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websiteiotdb.apache.orggithub.com/­datafuselabs/­databend
www.databend.com
www.h2database.comjsqldb.org (offline)www.timescale.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.databend.comwww.h2database.com/­html/­main.htmldocs.timescale.com
DeveloperApache Software FoundationDatabend LabsThomas MuellerKonrad von BackstromTimescale
Initial release20182021200520182017
Current release1.1.0, April 20231.0.59, April 20232.2.220, July 20230.8, December 20182.13.0, November 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infodual-licence (Mozilla public license, Eclipse public license)Open SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaRustJavaC
Server operating systemsAll OS with a Java VM (>= 1.8)hosted
Linux
macOS
All OS with a Java VMLinux
macOS
Windows
Linux
OS X
Windows
Data schemeyesyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesnonumerics, 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 indexesyesnoyesnoyes
SQL infoSupport of SQLSQL-like query languageyesyesnoyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
Native API
CLI Client
JDBC
RESTful HTTP API
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Go
Java
JavaScript (Node.js)
Python
Rust
JavaJavaScript.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyesnoJava Stored Procedures and User-Defined Functionsfunctions in JavaScriptuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyesnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)nonenonenoneyes, 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 replicasnoneWith clustering: 2 database servers on different computers operate on identical copies of a databasenoneSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyes infousing RocksDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlyesUsers with fine-grained authorization concept, user rolesfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Apache IoTDBDatabendH2JSqlDbTimescaleDB
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