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DBMS > Apache IoTDB vs. Datomic vs. Graph Engine vs. HBase vs. ReductStore

System Properties Comparison Apache IoTDB vs. Datomic vs. Graph Engine vs. HBase vs. ReductStore

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDatomic  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonHBase  Xexclude from comparisonReductStore  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 FlinkDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineWide-column store based on Apache Hadoop and on concepts of BigTableDesigned to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.
Primary database modelTime Series DBMSRelational DBMSGraph DBMS
Key-value store
Wide column storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score30.50
Rank#26  Overall
#2  Wide column stores
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Websiteiotdb.apache.orgwww.datomic.comwww.graphengine.iohbase.apache.orggithub.com/­reductstore
www.reduct.store
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.datomic.comwww.graphengine.io/­docs/­manualhbase.apache.org/­book.htmlwww.reduct.store/­docs
DeveloperApache Software FoundationCognitectMicrosoftApache Software Foundation infoApache top-level project, originally developed by PowersetReductStore LLC
Initial release20182012201020082023
Current release1.1.0, April 20231.0.6735, June 20232.3.4, January 20211.9, March 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infolimited edition freeOpen Source infoMIT LicenseOpen Source infoApache version 2Open Source infoBusiness Source License 1.1
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, Clojure.NET and CJavaC++, Rust
Server operating systemsAll OS with a Java VM (>= 1.8)All OS with a Java VM.NETLinux
Unix
Windows infousing Cygwin
Docker
Linux
macOS
Windows
Data schemeyesyesyesschema-free, schema definition possible
Typing infopredefined data types such as float or dateyesyesyesoptions to bring your own types, AVRO
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 indexesyesyesno
SQL infoSupport of SQLSQL-like query languagenonono
APIs and other access methodsJDBC
Native API
RESTful HTTP APIRESTful HTTP APIJava API
RESTful HTTP API
Thrift
HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Clojure
Java
C#
C++
F#
Visual Basic
C
C#
C++
Groovy
Java
PHP
Python
Scala
C++
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresyesyes infoTransaction Functionsyesyes infoCoprocessors in Java
TriggersyesBy using transaction functionsnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)none infoBut extensive use of caching in the application peershorizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasnone infoBut extensive use of caching in the application peersMulti-source replication
Source-replica 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 ConsistencyImmediate Consistency or Eventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoSingle row ACID (across millions of columns)
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes inforecommended only for testing and developmentyesyes
User concepts infoAccess controlyesnoAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

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More resources
Apache IoTDBDatomicGraph Engine infoformer name: TrinityHBaseReductStore
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