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DBMS > Apache IoTDB vs. Oracle Berkeley DB vs. Prometheus vs. Quasardb

System Properties Comparison Apache IoTDB vs. Oracle Berkeley DB vs. Prometheus vs. Quasardb

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonPrometheus  Xexclude from comparisonQuasardb  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 FlinkWidely used in-process key-value storeOpen-source Time Series DBMS and monitoring systemDistributed, high-performance timeseries database
Primary database modelTime Series DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Time Series DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Score0.21
Rank#322  Overall
#29  Time Series DBMS
Websiteiotdb.apache.orgwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlprometheus.ioquasar.ai
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.oracle.com/­cd/­E17076_05/­html/­index.htmlprometheus.io/­docsdoc.quasar.ai/­master
DeveloperApache Software FoundationOracle infooriginally developed by Sleepycat, which was acquired by Oraclequasardb
Initial release2018199420152009
Current release1.1.0, April 202318.1.40, May 20203.14.1, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infocommercial license availableOpen Source infoApache 2.0commercial 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 languageJavaC, Java, C++ (depending on the Berkeley DB edition)GoC++
Server operating systemsAll OS with a Java VM (>= 1.8)AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
Windows
BSD
Linux
OS X
Windows
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesnoNumeric data onlyyes 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.noyes infoonly with the Berkeley DB XML editionno infoImport of XML data possibleno
Secondary indexesyesyesnoyes infowith tags
SQL infoSupport of SQLSQL-like query languageyes infoSQL interfaced based on SQLite is availablenoSQL-like query language
APIs and other access methodsJDBC
Native API
RESTful HTTP/JSON APIHTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresyesnonono
Triggersyesyes infoonly for the SQL APInono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneShardingSharding 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 replicasSource-replica replicationyes infoby FederationSource-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonowith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
noneImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes infoTransient mode
User concepts infoAccess controlyesnonoCryptographically strong user authentication and audit trail

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More resources
Apache IoTDBOracle Berkeley DBPrometheusQuasardb
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