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DBMS > Apache IoTDB vs. Google Cloud Bigtable vs. Kinetica vs. TerminusDB

System Properties Comparison Apache IoTDB vs. Google Cloud Bigtable vs. Kinetica vs. TerminusDB

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonKinetica  Xexclude from comparisonTerminusDB infoformer name was DataChemist  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 FlinkGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Fully vectorized database across both GPUs and CPUsScalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships
Primary database modelTime Series DBMSKey-value store
Wide column store
Relational DBMSGraph DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.23
Rank#316  Overall
#27  Graph DBMS
Websiteiotdb.apache.orgcloud.google.com/­bigtablewww.kinetica.comterminusdb.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlcloud.google.com/­bigtable/­docsdocs.kinetica.comterminusdb.github.io/­terminusdb/­#
DeveloperApache Software FoundationGoogleKineticaDataChemist Ltd.
Initial release2018201520122018
Current release1.1.0, April 20237.1, August 202111.0.0, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++Prolog, Rust
Server operating systemsAll OS with a Java VM (>= 1.8)hostedLinuxLinux
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyes
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.nononono
Secondary indexesyesnoyes
SQL infoSupport of SQLSQL-like query languagenoSQL-like DML and DDL statementsSQL-like query language (WOQL)
APIs and other access methodsJDBC
Native API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
RESTful HTTP API
OWL
RESTful HTTP API
WOQL (Web Object Query Language)
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
JavaScript (Node.js)
Python
JavaScript
Python
Server-side scripts infoStored proceduresyesnouser defined functionsyes
Triggersyesnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingGraph Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationJournaling Streams
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoin-memory journaling
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infoGPU vRAM or System RAM
User concepts infoAccess controlyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles on table levelRole-based access control

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More resources
Apache IoTDBGoogle Cloud BigtableKineticaTerminusDB infoformer name was DataChemist
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