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DBMS > Apache IoTDB vs. Hazelcast vs. Hyprcubd vs. Ingres vs. Yanza

System Properties Comparison Apache IoTDB vs. Hazelcast vs. Hyprcubd vs. Ingres vs. Yanza

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonHazelcast  Xexclude from comparisonHyprcubd  Xexclude from comparisonIngres  Xexclude from comparisonYanza  Xexclude from comparison
Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.Yanza seems to be discontinued. Therefore it is excluded 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 FlinkA widely adopted in-memory data gridServerless Time Series DBMSWell established RDBMSTime Series DBMS for IoT Applications
Primary database modelTime Series DBMSKey-value storeTime Series DBMSRelational DBMSTime Series DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score3.80
Rank#82  Overall
#44  Relational DBMS
Websiteiotdb.apache.orghazelcast.comhyprcubd.com (offline)www.actian.com/­databases/­ingresyanza.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlhazelcast.org/­imdg/­docsdocs.actian.com/­ingres
DeveloperApache Software FoundationHazelcastHyprcubd, Inc.Actian CorporationYanza
Initial release201820081974 infooriginally developed at University Berkely in early 1970s2015
Current release1.1.0, April 20235.3.6, November 202311.2, May 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2; commercial licenses availablecommercialcommercialcommercial infofree version available
Cloud-based only infoOnly available as a cloud servicenonoyesnono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaGoC
Server operating systemsAll OS with a Java VM (>= 1.8)All OS with a Java VMhostedAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Windows
Data schemeyesschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyes infotime, int, uint, float, stringyesno
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 infothe object must implement a serialization strategynono infobut tools for importing/exporting data from/to XML-files availableno
Secondary indexesyesyesnoyesno
SQL infoSupport of SQLSQL-like query languageSQL-like query languageSQL-like query languageyesno
APIs and other access methodsJDBC
Native API
JCache
JPA
Memcached protocol
RESTful HTTP API
gRPC (https).NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
any language that supports HTTP calls
Server-side scripts infoStored proceduresyesyes infoEvent Listeners, Executor Servicesnoyesno
Triggersyesyes infoEventsnoyesyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslynone
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 infoReplicated MapIngres Replicatornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoone or two-phase-commit; repeatable reads; read commitednoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesnoyes infoMVCCyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnono
User concepts infoAccess controlyesRole-based access controltoken accessfine grained access rights according to SQL-standardno

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More resources
Apache IoTDBHazelcastHyprcubdIngresYanza
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