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DBMS > Apache IoTDB vs. BigchainDB vs. Drizzle vs. Kinetica vs. TerarkDB

System Properties Comparison Apache IoTDB vs. BigchainDB vs. Drizzle vs. Kinetica vs. TerarkDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonBigchainDB  Xexclude from comparisonDrizzle  Xexclude from comparisonKinetica  Xexclude from comparisonTerarkDB  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded 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 FlinkBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Fully vectorized database across both GPUs and CPUsA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelTime Series DBMSDocument storeRelational DBMSRelational DBMSKey-value store
Secondary database modelsSpatial DBMS
Time Series 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
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websiteiotdb.apache.orgwww.bigchaindb.comwww.kinetica.comgithub.com/­bytedance/­terarkdb
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlbigchaindb.readthedocs.io/­en/­latestdocs.kinetica.combytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperApache Software FoundationDrizzle project, originally started by Brian AkerKineticaByteDance, originally Terark
Initial release20182016200820122016
Current release1.1.0, April 20237.2.4, September 20127.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoAGPL v3Open Source infoGNU GPLcommercialcommercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaPythonC++C, C++C++
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxFreeBSD
Linux
OS X
Linux
Data schemeyesschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesnoyesyesno
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 indexesyesyesyesno
SQL infoSupport of SQLSQL-like query languagenoyes infowith proprietary extensionsSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
Native API
CLI Client
RESTful HTTP API
JDBCJDBC
ODBC
RESTful HTTP API
C++ API
Java API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Go
Haskell
Java
JavaScript
Python
Ruby
C
C++
Java
PHP
C++
Java
JavaScript (Node.js)
Python
C++
Java
Server-side scripts infoStored proceduresyesnouser defined functionsno
Triggersyesno infohooks for callbacks inside the server can be used.yes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingShardingnone
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 factorMulti-source replication
Source-replica replication
Source-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnono
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.yesyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlyesyesPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users and roles on table levelno

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More resources
Apache IoTDBBigchainDBDrizzleKineticaTerarkDB
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