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

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

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonQuestDB  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 engineA high performance open source SQL database for time series dataOpen Source Operational and Transactional Enterprise NoSQL Document Database
Primary database modelTime Series DBMSGraph DBMS
Key-value store
Time Series DBMSDocument store
Secondary database modelsRelational DBMSGraph 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
Score2.70
Rank#105  Overall
#8  Time Series DBMS
Score2.84
Rank#101  Overall
#18  Document stores
Websiteiotdb.apache.orgwww.graphengine.ioquestdb.ioravendb.net
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.graphengine.io/­docs/­manualquestdb.io/­docsravendb.net/­docs
DeveloperApache Software FoundationMicrosoftQuestDB Technology IncHibernating Rhinos
Initial release2018201020142010
Current release1.1.0, April 20235.4, July 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoMIT LicenseOpen Source infoApache 2.0Open Source infoAGPL version 3, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava.NET and CJava (Zero-GC), C++, RustC#
Server operating systemsAll OS with a Java VM (>= 1.8).NETLinux
macOS
Windows
Linux
macOS
Raspberry Pi
Windows
Data schemeyesyesyes infoschema-free via InfluxDB Line Protocolschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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 indexesyesnoyes
SQL infoSupport of SQLSQL-like query languagenoSQL with time-series extensionsSQL-like query language (RQL)
APIs and other access methodsJDBC
Native API
RESTful HTTP APIHTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
.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 infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesyesnoyes
Triggersyesnonoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal partitioninghorizontal partitioning (by timestamps)Sharding
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 replication with eventual consistencyMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyDefault 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 for single-table writesACID, 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 infothrough memory mapped files
User concepts infoAccess controlyesAuthorization levels configured per client per database
More information provided by the system vendor
Apache IoTDBGraph Engine infoformer name: TrinityQuestDBRavenDB
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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Apache IoTDBGraph Engine infoformer name: TrinityQuestDBRavenDB
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