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DBMS > Apache IoTDB vs. BigchainDB vs. DataFS vs. Elasticsearch vs. EXASOL

System Properties Comparison Apache IoTDB vs. BigchainDB vs. DataFS vs. Elasticsearch vs. EXASOL

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonBigchainDB  Xexclude from comparisonDataFS  Xexclude from comparisonElasticsearch  Xexclude from comparisonEXASOL  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 FlinkBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsAll data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.A distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.
Primary database modelTime Series DBMSDocument storeObject oriented DBMSSearch engineRelational DBMS
Secondary database modelsGraph DBMSDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.79
Rank#212  Overall
#36  Document stores
Score0.06
Rank#354  Overall
#15  Object oriented DBMS
Score135.35
Rank#7  Overall
#1  Search engines
Score1.99
Rank#124  Overall
#58  Relational DBMS
Websiteiotdb.apache.orgwww.bigchaindb.comnewdatabase.comwww.elastic.co/­elasticsearchwww.exasol.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlbigchaindb.readthedocs.io/­en/­latestdev.mobiland.com/­Overview.xspwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlwww.exasol.com/­resources
DeveloperApache Software FoundationMobiland AGElasticExasol
Initial release20182016201820102000
Current release1.1.0, April 20231.1.263, October 20228.6, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoAGPL v3commercialOpen Source infoElastic Licensecommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaPythonJava
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxWindowsAll OS with a Java VM
Data schemeyesschema-freeClasses, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)schema-free infoFlexible type definitions. Once a type is defined, it is persistentyes
Typing infopredefined data types such as float or dateyesnoyesyesyes
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.nonononono
Secondary indexesyesnoyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLSQL-like query languagenonoSQL-like query languageyes
APIs and other access methodsJDBC
Native API
CLI Client
RESTful HTTP API
.NET Client API
Proprietary client DLL
WinRT client
Java API
RESTful HTTP/JSON API
.Net
JDBC
ODBC
WebSocket
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Go
Haskell
Java
JavaScript
Python
Ruby
.Net
C
C#
C++
VB.Net
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
Java
Lua
Python
R
Server-side scripts infoStored proceduresyesyesuser defined functions
Triggersyesno, except callback-events from server when changes happenedyes infoby using the 'percolation' featureyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingProprietary Sharding systemShardingSharding
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 factoryes
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparknonoES-Hadoop Connectoryes infoHadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes,with MongoDB ord RethinkDByesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoMemcached and Redis integrationyes
User concepts infoAccess controlyesyesWindows-ProfileAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache IoTDBBigchainDBDataFSElasticsearchEXASOL
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