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DBMS > Apache IoTDB vs. Netezza vs. Stardog vs. Vitess

System Properties Comparison Apache IoTDB vs. Netezza vs. Stardog vs. Vitess

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonStardog  Xexclude from comparisonVitess  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 FlinkData warehouse and analytics appliance part of IBM PureSystemsEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualizationScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelTime Series DBMSRelational DBMSGraph DBMS
RDF store
Relational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websiteiotdb.apache.orgwww.ibm.com/­products/­netezzawww.stardog.comvitess.io
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.stardog.comvitess.io/­docs
DeveloperApache Software FoundationIBMStardog-UnionThe Linux Foundation, PlanetScale
Initial release2018200020102013
Current release1.1.0, April 20237.3.0, May 202015.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/studentsOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaGo
Server operating systemsAll OS with a Java VM (>= 1.8)Linux infoincluded in applianceLinux
macOS
Windows
Docker
Linux
macOS
Data schemeyesyesschema-free and OWL/RDFS-schema supportyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nono infoImport/export of XML data possible
Secondary indexesyesyesyes infosupports real-time indexing in full-text and geospatialyes
SQL infoSupport of SQLSQL-like query languageyesYes, compatible with all major SQL variants through dedicated BI/SQL Serveryes infowith proprietary extensions
APIs and other access methodsJDBC
Native API
JDBC
ODBC
OLE DB
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C++
Fortran
Java
Lua
Perl
Python
R
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyesyesuser defined functions and aggregates, HTTP Server extensions in Javayes infoproprietary syntax
Triggersyesnoyes infovia event handlersyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingnoneSharding
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 replicationMulti-source replication in HA-ClusterMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency in HA-ClusterEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynonoyes inforelationships in graphsyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlyesUsers with fine-grained authorization conceptAccess rights for users and rolesUsers with fine-grained authorization concept infono user groups or roles

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More resources
Apache IoTDBNetezza infoAlso called PureData System for Analytics by IBMStardogVitess
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