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DBMS > Apache IoTDB vs. Datomic vs. H2 vs. HarperDB

System Properties Comparison Apache IoTDB vs. Datomic vs. H2 vs. HarperDB

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDatomic  Xexclude from comparisonH2  Xexclude from comparisonHarperDB  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 FlinkDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityFull-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.
Primary database modelTime Series DBMSRelational DBMSRelational DBMSDocument store
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score8.13
Rank#49  Overall
#31  Relational DBMS
Score0.55
Rank#248  Overall
#38  Document stores
Websiteiotdb.apache.orgwww.datomic.comwww.h2database.comwww.harperdb.io
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.datomic.comwww.h2database.com/­html/­main.htmldocs.harperdb.io/­docs
DeveloperApache Software FoundationCognitectThomas MuellerHarperDB
Initial release2018201220052017
Current release1.1.0, April 20231.0.6735, June 20232.2.220, July 20233.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infolimited edition freeOpen Source infodual-licence (Mozilla public license, Eclipse public license)commercial infofree community edition available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, ClojureJavaNode.js
Server operating systemsAll OS with a Java VM (>= 1.8)All OS with a Java VMAll OS with a Java VMLinux
OS X
Data schemeyesyesyesdynamic schema
Typing infopredefined data types such as float or dateyesyesyesyes infoJSON 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.nononono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query languagenoyesSQL-like data manipulation statements
APIs and other access methodsJDBC
Native API
RESTful HTTP APIJDBC
ODBC
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Clojure
Java
Java.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
Server-side scripts infoStored proceduresyesyes infoTransaction FunctionsJava Stored Procedures and User-Defined FunctionsCustom Functions infosince release 3.1
TriggersyesBy using transaction functionsyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)none infoBut extensive use of caching in the application peersnoneA table resides as a whole on one (or more) nodes in a cluster
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasnone infoBut extensive use of caching in the application peersWith clustering: 2 database servers on different computers operate on identical copies of a databaseyes infothe nodes on which a table resides can be defined
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 integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDAtomic execution of specific operations
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes, using LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes inforecommended only for testing and developmentyesyes
User concepts infoAccess controlyesnofine grained access rights according to SQL-standardAccess rights for users and roles

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More resources
Apache IoTDBDatomicH2HarperDB
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