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DBMS > Apache IoTDB vs. HarperDB vs. Hypertable vs. Quasardb

System Properties Comparison Apache IoTDB vs. HarperDB vs. Hypertable vs. Quasardb

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonHarperDB  Xexclude from comparisonHypertable  Xexclude from comparisonQuasardb  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed 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 FlinkUltra-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.An open source BigTable implementation based on distributed file systems such as HadoopDistributed, high-performance timeseries database
Primary database modelTime Series DBMSDocument storeWide column storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.60
Rank#244  Overall
#38  Document stores
Score0.21
Rank#322  Overall
#29  Time Series DBMS
Websiteiotdb.apache.orgwww.harperdb.ioquasar.ai
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.harperdb.io/­docsdoc.quasar.ai/­master
DeveloperApache Software FoundationHarperDBHypertable Inc.quasardb
Initial release2018201720092009
Current release1.1.0, April 20233.1, August 20210.9.8.11, March 20163.14.1, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree community edition availableOpen Source infoGNU version 3. Commercial license availablecommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaNode.jsC++C++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Linux
OS X
Windows infoan inofficial Windows port is available
BSD
Linux
OS X
Windows
Data schemeyesdynamic schemaschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes infoJSON data typesnoyes infointeger and binary
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.nonono
Secondary indexesyesyesrestricted infoonly exact value or prefix value scansyes infowith tags
SQL infoSupport of SQLSQL-like query languageSQL-like data manipulation statementsnoSQL-like query language
APIs and other access methodsJDBC
Native API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
C++ API
Thrift
HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.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
C++
Java
Perl
PHP
Python
Ruby
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresyesCustom Functions infosince release 3.1nono
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)A table resides as a whole on one (or more) nodes in a clusterShardingSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyes infothe nodes on which a table resides can be definedselectable replication factor on file system levelSource-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyeswith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByesyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes infoTransient mode
User concepts infoAccess controlyesAccess rights for users and rolesnoCryptographically strong user authentication and audit trail

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More resources
Apache IoTDBHarperDBHypertableQuasardb
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