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DBMS > Apache IoTDB vs. Hypertable vs. Kinetica vs. SpaceTime vs. Teradata Aster

System Properties Comparison Apache IoTDB vs. Hypertable vs. Kinetica vs. SpaceTime vs. Teradata Aster

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonHypertable  Xexclude from comparisonKinetica  Xexclude from comparisonSpaceTime  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.Teradata Aster has been integrated into other Teradata systems and therefore will be 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 HadoopFully vectorized database across both GPUs and CPUsSpaceTime is a spatio-temporal DBMS with a focus on performance.Platform for big data analytics on multistructured data sources and types
Primary database modelTime Series DBMSWide column storeRelational DBMSSpatial DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.00
Rank#383  Overall
#7  Spatial DBMS
Websiteiotdb.apache.orgwww.kinetica.comwww.mireo.com/­spacetime
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.kinetica.com
DeveloperApache Software FoundationHypertable Inc.KineticaMireoTeradata
Initial release20182009201220202005
Current release1.1.0, April 20230.9.8.11, March 20167.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGNU version 3. Commercial license availablecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C, C++C++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Windows infoan inofficial Windows port is available
LinuxLinuxLinux
Data schemeyesschema-freeyesyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesnoyesyesyes
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.nononoyes infoin Aster File Store
Secondary indexesyesrestricted infoonly exact value or prefix value scansyesnoyes
SQL infoSupport of SQLSQL-like query languagenoSQL-like DML and DDL statementsA subset of ANSI SQL is implementedyes
APIs and other access methodsJDBC
Native API
C++ API
Thrift
JDBC
ODBC
RESTful HTTP API
RESTful HTTP APIADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C++
Java
Perl
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
C#
C++
Python
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyesnouser defined functionsnoR packages
Triggersyesnoyes infotriggers when inserted values for one or more columns fall within a specified rangenono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingFixed-grid hypercubesSharding
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 levelSource-replica replicationReal-time block device replication (DRBD)yes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesnonoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.yesyes infoGPU vRAM or System RAMnono
User concepts infoAccess controlyesnoAccess rights for users and roles on table levelyesfine grained access rights according to SQL-standard

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More resources
Apache IoTDBHypertableKineticaSpaceTimeTeradata Aster
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