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DBMS > Apache IoTDB vs. Graph Engine vs. GridDB vs. RavenDB

System Properties Comparison Apache IoTDB vs. Graph Engine vs. GridDB vs. RavenDB

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonGridDB  Xexclude from comparisonRavenDB  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 FlinkA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineScalable in-memory time series database optimized for IoT and Big DataOpen Source Operational and Transactional Enterprise NoSQL Document Database
Primary database modelTime Series DBMSGraph DBMS
Key-value store
Time Series DBMSDocument store
Secondary database modelsKey-value store
Relational DBMS
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.67
Rank#232  Overall
#21  Graph DBMS
#34  Key-value stores
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score2.84
Rank#101  Overall
#18  Document stores
Websiteiotdb.apache.orgwww.graphengine.iogriddb.netravendb.net
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.graphengine.io/­docs/­manualdocs.griddb.netravendb.net/­docs
DeveloperApache Software FoundationMicrosoftToshiba CorporationHibernating Rhinos
Initial release2018201020132010
Current release1.1.0, April 20235.1, August 20225.4, July 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoMIT LicenseOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoAGPL version 3, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava.NET and CC++C#
Server operating systemsAll OS with a Java VM (>= 1.8).NETLinuxLinux
macOS
Raspberry Pi
Windows
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampno
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.nonono
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like query languagenoSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query language (RQL)
APIs and other access methodsJDBC
Native API
RESTful HTTP APIJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
C++
F#
Visual Basic
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesyesnoyes
Triggersyesnoyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal partitioningShardingSharding
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 replicationMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparkConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate consistency within container, eventual consistency across containersDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID at container levelACID, Cluster-wide transaction available
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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 storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlyesAccess rights for users can be defined per databaseAuthorization levels configured per client per database
More information provided by the system vendor
Apache IoTDBGraph Engine infoformer name: TrinityGridDBRavenDB
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Apache IoTDBGraph Engine infoformer name: TrinityGridDBRavenDB
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