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

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

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonHarperDB  Xexclude from comparisonQuasardb  Xexclude from comparisonSequoiadb  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 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.Distributed, high-performance timeseries databaseNewSQL database with distributed OLTP and SQL
Primary database modelTime Series DBMSDocument storeTime Series DBMSDocument store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.55
Rank#248  Overall
#38  Document stores
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score0.45
Rank#261  Overall
#41  Document stores
#122  Relational DBMS
Websiteiotdb.apache.orgwww.harperdb.ioquasar.aiwww.sequoiadb.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.harperdb.io/­docsdoc.quasar.ai/­masterwww.sequoiadb.com/­en/­index.php?m=Files&a=index
DeveloperApache Software FoundationHarperDBquasardbSequoiadb Ltd.
Initial release2018201720092013
Current release1.1.0, April 20233.1, August 20213.14.1, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree community edition availablecommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoServer: AGPL; Client: Apache V2
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
BSD
Linux
OS X
Windows
Linux
Data schemeyesdynamic schemaschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes infoJSON data typesyes infointeger and binaryyes infooid, date, timestamp, binary, regex
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 indexesyesyesyes infowith tagsyes
SQL infoSupport of SQLSQL-like query languageSQL-like data manipulation statementsSQL-like query languageSQL-like query language
APIs and other access methodsJDBC
Native API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
HTTP APIproprietary protocol using JSON
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
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
.Net
C++
Java
PHP
Python
Server-side scripts infoStored proceduresyesCustom Functions infosince release 3.1noJavaScript
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 clusterSharding infoconsistent hashingSharding
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 definedSource-replica replication with selectable replication factorSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknowith Hadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsACIDDocument is locked during a transaction
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByes infoby using LevelDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes infoTransient modeno
User concepts infoAccess controlyesAccess rights for users and rolesCryptographically strong user authentication and audit trailsimple password-based access control

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More resources
Apache IoTDBHarperDBQuasardbSequoiadb
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