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DBMS > Apache IoTDB vs. Graph Engine vs. Kinetica vs. SpaceTime vs. Teradata Aster

System Properties Comparison Apache IoTDB vs. Graph Engine vs. Kinetica vs. SpaceTime vs. Teradata Aster

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonKinetica  Xexclude from comparisonSpaceTime  Xexclude from comparisonTeradata Aster  Xexclude from comparison
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 FlinkA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineFully 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 DBMSGraph DBMS
Key-value store
Relational 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
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.00
Rank#383  Overall
#7  Spatial DBMS
Websiteiotdb.apache.orgwww.graphengine.iowww.kinetica.comwww.mireo.com/­spacetime
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.graphengine.io/­docs/­manualdocs.kinetica.com
DeveloperApache Software FoundationMicrosoftKineticaMireoTeradata
Initial release20182010201220202005
Current release1.1.0, April 20237.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoMIT Licensecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava.NET and CC, C++C++
Server operating systemsAll OS with a Java VM (>= 1.8).NETLinuxLinuxLinux
Data schemeyesyesyesyesFlexible 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 dateyesyesyesyesyes
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.nonononoyes infoin Aster File Store
Secondary indexesyesyesnoyes
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
RESTful HTTP APIJDBC
ODBC
RESTful HTTP API
RESTful HTTP APIADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
C++
F#
Visual Basic
C++
Java
JavaScript (Node.js)
Python
C#
C++
Python
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyesyesuser 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)horizontal partitioningShardingFixed-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 replicasSource-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 Sparknonoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate 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 persistentyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes infoGPU vRAM or System RAMnono
User concepts infoAccess controlyesAccess rights for users and roles on table levelyesfine grained access rights according to SQL-standard

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More resources
Apache IoTDBGraph Engine infoformer name: TrinityKineticaSpaceTimeTeradata Aster
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