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DBMS > Apache IoTDB vs. Datomic vs. Hazelcast vs. Microsoft Azure Table Storage vs. UniData,UniVerse

System Properties Comparison Apache IoTDB vs. Datomic vs. Hazelcast vs. Microsoft Azure Table Storage vs. UniData,UniVerse

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDatomic  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonUniData,UniVerse  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 FlinkDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA widely adopted in-memory data gridA Wide Column Store for rapid development using massive semi-structured datasetsMultiValue database and application server with SQL mapping layer and meta database capabilities
Primary database modelTime Series DBMSRelational DBMSKey-value storeWide column storeMultivalue DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score4.48
Rank#75  Overall
#6  Wide column stores
Score3.16
Rank#97  Overall
#2  Multivalue DBMS
Websiteiotdb.apache.orgwww.datomic.comhazelcast.comazure.microsoft.com/­en-us/­services/­storage/­tableswww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-unidata
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.datomic.comhazelcast.org/­imdg/­docsdocs.rocketsoftware.com/­bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata
DeveloperApache Software FoundationCognitectHazelcastMicrosoftRocket Software
Initial release20182012200820121985
Current release1.1.0, April 20231.0.6735, June 20235.3.6, November 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infolimited edition freeOpen Source infoApache Version 2; commercial licenses availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava, ClojureJavaC
Server operating systemsAll OS with a Java VM (>= 1.8)All OS with a Java VMAll OS with a Java VMhostedAIX
HP-UX
Linux
Solaris
Windows
Data schemeyesyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesyesoptional
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.nonoyes infothe object must implement a serialization strategyno
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLSQL-like query languagenoSQL-like query languagenoyes
APIs and other access methodsJDBC
Native API
RESTful HTTP APIJCache
JPA
Memcached protocol
RESTful HTTP API
RESTful HTTP APIJava API infoJPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Clojure
Java
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Basic infoU2 Basic
C
Java
Server-side scripts infoStored proceduresyesyes infoTransaction Functionsyes infoEvent Listeners, Executor Servicesnoyes
TriggersyesBy using transaction functionsyes infoEventsnoyes infoU2 Basic
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)none infoBut extensive use of caching in the application peersShardingSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasnone infoBut extensive use of caching in the application peersyes infoReplicated Mapyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication
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 ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDone or two-phase-commit; repeatable reads; read commitedoptimistic lockingACID infoconfigurable
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes inforecommended only for testing and developmentyesno
User concepts infoAccess controlyesnoRole-based access controlAccess rights based on private key authentication or shared access signaturesAccess rights according to SQL-standard and operating system based

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Apache IoTDBDatomicHazelcastMicrosoft Azure Table StorageUniData,UniVerse
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