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DBMS > Apache IoTDB vs. Apache Kylin vs. Dgraph vs. Faircom DB vs. TerarkDB

System Properties Comparison Apache IoTDB vs. Apache Kylin vs. Dgraph vs. Faircom DB vs. TerarkDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonApache Kylin  Xexclude from comparisonDgraph  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonTerarkDB  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 analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackDistributed and scalable native Graph DBMSNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.A 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 DBMSRelational DBMSGraph DBMSKey-value store
Relational DBMS
Key-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score1.18
Rank#172  Overall
#79  Relational DBMS
Score1.45
Rank#156  Overall
#15  Graph DBMS
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websiteiotdb.apache.orgkylin.apache.orgdgraph.iowww.faircom.com/­products/­faircom-dbgithub.com/­bytedance/­terarkdb
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlkylin.apache.org/­docsdgraph.io/­docsdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperApache Software FoundationApache Software Foundation, originally contributed from eBay IncDgraph Labs, Inc.FairCom CorporationByteDance, originally Terark
Initial release20182015201619792016
Current release1.1.0, April 20233.1.0, July 2020V12, November 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoApache 2.0commercial infoRestricted, free version availablecommercial 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 languageJavaJavaGoANSI C, C++C++
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxLinux
OS X
Windows
AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Data schemeyesyesschema-freeschema free, schema optional, schema required, partial schema,schema-free
Typing infopredefined data types such as float or dateyesyesyesyes, ANSI SQL Types, JSON, typed binary structuresno
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 indexesyesyesyesyesno
SQL infoSupport of SQLSQL-like query languageANSI SQL for queries (using Apache Calcite)noyes, ANSI SQL with proprietary extensionsno
APIs and other access methodsJDBC
Native API
JDBC
ODBC
RESTful HTTP API
GraphQL query language
gRPC (using protocol buffers) API
HTTP API
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
C++ API
Java API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C++
Java
Server-side scripts infoStored proceduresyesnoyes info.Net, JavaScript, C/C++no
Triggersyesnoyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)yesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasSynchronous replication via Raftyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).none
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDtunable from ACID to Eventually Consistentno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesYes, tunable from durable to delayed durability to in-memoryyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyes
User concepts infoAccess controlyesno infoPlanned for future releasesFine grained access rights according to SQL-standard with additional protections for filesno

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More resources
Apache IoTDBApache KylinDgraphFaircom DB infoformerly c-treeACETerarkDB
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