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DBMS > Apache IoTDB vs. Hypertable vs. Ingres vs. Riak KV

System Properties Comparison Apache IoTDB vs. Hypertable vs. Ingres vs. Riak KV

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonHypertable  Xexclude from comparisonIngres  Xexclude from comparisonRiak KV  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed 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 FlinkAn open source BigTable implementation based on distributed file systems such as HadoopWell established RDBMSDistributed, fault tolerant key-value store
Primary database modelTime Series DBMSWide column storeRelational DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexes
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score4.11
Rank#81  Overall
#44  Relational DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Websiteiotdb.apache.orgwww.actian.com/­databases/­ingres
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.actian.com/­ingreswww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperApache Software FoundationHypertable Inc.Actian CorporationOpenSource, formerly Basho Technologies
Initial release201820091974 infooriginally developed at University Berkely in early 1970s2009
Current release1.1.0, April 20230.9.8.11, March 201611.2, May 20223.2.0, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGNU version 3. Commercial license availablecommercialOpen Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++CErlang
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Windows infoan inofficial Windows port is available
AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Linux
OS X
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesnoyesno
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 infobut tools for importing/exporting data from/to XML-files availableno
Secondary indexesyesrestricted infoonly exact value or prefix value scansyesrestricted
SQL infoSupport of SQLSQL-like query languagenoyesno
APIs and other access methodsJDBC
Native API
C++ API
Thrift
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
HTTP API
Native Erlang Interface
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C++
Java
Perl
PHP
Python
Ruby
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresyesnoyesErlang
Triggersyesnoyesyes infopre-commit hooks and post-commit hooks
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 simultaneouslySharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasselectable replication factor on file system levelIngres Replicatorselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyesno infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCCyes
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.yesno
User concepts infoAccess controlyesnofine grained access rights according to SQL-standardyes, using Riak Security

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Apache IoTDBHypertableIngresRiak KV
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