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DBMS > Apache IoTDB vs. Hazelcast vs. HugeGraph vs. Sphinx vs. Trafodion

System Properties Comparison Apache IoTDB vs. Hazelcast vs. HugeGraph vs. Sphinx vs. Trafodion

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonHazelcast  Xexclude from comparisonHugeGraph  Xexclude from comparisonSphinx  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. 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 gridA fast-speed and highly-scalable Graph DBMSOpen source search engine for searching in data from different sources, e.g. relational databasesTransactional SQL-on-Hadoop DBMS
Primary database modelTime Series DBMSKey-value storeGraph DBMSSearch engineRelational 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
Score5.97
Rank#57  Overall
#6  Key-value stores
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websiteiotdb.apache.orghazelcast.comgithub.com/­hugegraph
hugegraph.apache.org
sphinxsearch.comtrafodion.apache.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlhazelcast.org/­imdg/­docshugegraph.apache.org/­docssphinxsearch.com/­docstrafodion.apache.org/­documentation.html
DeveloperApache Software FoundationHazelcastBaiduSphinx Technologies Inc.Apache Software Foundation, originally developed by HP
Initial release20182008201820012014
Current release1.1.0, April 20235.3.6, November 20230.93.5.1, February 20232.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2; commercial licenses availableOpen Source infoApache Version 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoApache 2.0
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 languageJavaJavaJavaC++C++, Java
Server operating systemsAll OS with a Java VM (>= 1.8)All OS with a Java VMLinux
macOS
Unix
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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
Secondary indexesyesyesyes infoalso supports composite index and range indexyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-like query languageSQL-like query languagenoSQL-like query language (SphinxQL)yes
APIs and other access methodsJDBC
Native API
JCache
JPA
Memcached protocol
RESTful HTTP API
Java API
RESTful HTTP API
TinkerPop Gremlin
Proprietary protocolADO.NET
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Groovy
Java
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresyesyes infoEvent Listeners, Executor Servicesasynchronous Gremlin script jobsnoJava Stored Procedures
Triggersyesyes infoEventsnonono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardingyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
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 Mapyes infodepending on used storage backend, e.g. Cassandra and HBasenoneyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesvia hugegraph-sparknoyes infovia user defined functions and HBase
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 Consistency
Foreign keys infoReferential integritynonoyes infoedges in graphnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoone or two-phase-commit; repeatable reads; read commitedACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesno
User concepts infoAccess controlyesRole-based access controlUsers, roles and permissionsnofine grained access rights according to SQL-standard

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Apache IoTDBHazelcastHugeGraphSphinxTrafodion
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