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DBMS > Apache IoTDB vs. HarperDB vs. Percona Server for MongoDB vs. Postgres-XL vs. RocksDB

System Properties Comparison Apache IoTDB vs. HarperDB vs. Percona Server for MongoDB vs. Postgres-XL vs. RocksDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonHarperDB  Xexclude from comparisonPercona Server for MongoDB  Xexclude from comparisonPostgres-XL  Xexclude from comparisonRocksDB  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 FlinkHarperDB takes the "stack" out of "tech stack" by combining an ultra-fast document-style data store, in-memory cache, real-time message broker, and your application components into a single distributed technology.A drop-in replacement for MongoDB Community Edition with enterprise-grade features.Based on PostgreSQL enhanced with MPP and write-scale-out cluster featuresEmbeddable persistent key-value store optimized for fast storage (flash and RAM)
Primary database modelTime Series DBMSDocument storeDocument storeRelational DBMSKey-value store
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#159  Overall
#14  Time Series DBMS
Score0.55
Rank#243  Overall
#38  Document stores
Score0.50
Rank#250  Overall
#39  Document stores
Score0.43
Rank#260  Overall
#119  Relational DBMS
Score2.84
Rank#97  Overall
#16  Key-value stores
Websiteiotdb.apache.orgwww.harperdb.iowww.percona.com/­mongodb/­software/­percona-server-for-mongodbwww.postgres-xl.orgrocksdb.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.harperdb.io/­docsdocs.percona.com/­percona-distribution-for-mongodbwww.postgres-xl.org/­documentationgithub.com/­facebook/­rocksdb/­wiki
DeveloperApache Software FoundationHarperDBPerconaFacebook, Inc.
Initial release2018201720152014 infosince 2012, originally named StormDB2013
Current release1.1.0, April 20233.1, August 20213.4.10-2.10, November 201710 R1, October 20189.4.0, June 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree community edition availableOpen Source infoGPL Version 2Open Source infoMozilla public licenseOpen Source infoBSD
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 languageJavaNode.jsC++CC++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
LinuxLinux
macOS
Linux
Data schemeyesdynamic schemaschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyes infoJSON data typesyesyesno
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.nononoyes infoXML type, but no XML query functionalityno
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLSQL-like query languageSQL-like data manipulation statementsnoyes infodistributed, parallel query executionno
APIs and other access methodsJDBC
Native API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
proprietary protocol using JSONADO.NET
JDBC
native C library
ODBC
streaming API for large objects
C++ API
Java 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
Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C++
Go
Java
Perl
Python
Ruby
Server-side scripts infoStored proceduresyesCustom Functions infosince release 3.1JavaScriptuser defined functionsno
Triggersyesnonoyes
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 clusterShardinghorizontal partitioninghorizontal partitioning
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 replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsnoACID infoMVCCyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes infovia In-Memory Enginenoyes
User concepts infoAccess controlyesAccess rights for users and rolesAccess rights for users and rolesfine grained access rights according to SQL-standardno

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More resources
Apache IoTDBHarperDBPercona Server for MongoDBPostgres-XLRocksDB
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