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DBMS > Apache IoTDB vs. Graph Engine vs. Hypertable vs. Solr

System Properties Comparison Apache IoTDB vs. Graph Engine vs. Hypertable vs. Solr

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonHypertable  Xexclude from comparisonSolr  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is 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 engineAn open source BigTable implementation based on distributed file systems such as HadoopA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelTime Series DBMSGraph DBMS
Key-value store
Wide column storeSearch engine
Secondary database modelsSpatial 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
Score41.02
Rank#24  Overall
#3  Search engines
Websiteiotdb.apache.orgwww.graphengine.iosolr.apache.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.graphengine.io/­docs/­manualsolr.apache.org/­resources.html
DeveloperApache Software FoundationMicrosoftHypertable Inc.Apache Software Foundation
Initial release2018201020092006
Current release1.1.0, April 20230.9.8.11, March 20169.6.1, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoMIT LicenseOpen Source infoGNU version 3. Commercial license availableOpen Source infoApache Version 2
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++Java
Server operating systemsAll OS with a Java VM (>= 1.8).NETLinux
OS X
Windows infoan inofficial Windows port is available
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesyesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesnoyes infosupports customizable data types and automatic typing
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.nonoyes
Secondary indexesyesrestricted infoonly exact value or prefix value scansyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like query languagenonoSolr Parallel SQL Interface
APIs and other access methodsJDBC
Native API
RESTful HTTP APIC++ API
Thrift
Java API
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
C++
F#
Visual Basic
C++
Java
Perl
PHP
Python
Ruby
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyesyesnoJava plugins
Triggersyesnonoyes infoUser configurable commands triggered on index changes
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 replicasselectable replication factor on file system levelyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononooptimistic locking
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 controlyesnoyes

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More resources
Apache IoTDBGraph Engine infoformer name: TrinityHypertableSolr
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