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DBMS > Apache Doris vs. Apache IoTDB vs. Ehcache vs. Faircom DB

System Properties Comparison Apache Doris vs. Apache IoTDB vs. Ehcache vs. Faircom DB

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NameApache Doris  Xexclude from comparisonApache IoTDB  Xexclude from comparisonEhcache  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparison
DescriptionAn MPP-based analytics DBMS embracing the MySQL protocolAn 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 widely adopted Java cache with tiered storage optionsNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.
Primary database modelRelational DBMSTime Series DBMSKey-value storeKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.57
Rank#244  Overall
#113  Relational DBMS
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score4.89
Rank#67  Overall
#8  Key-value stores
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Websitedoris.apache.org
github.com/­apache/­doris
iotdb.apache.orgwww.ehcache.orgwww.faircom.com/­products/­faircom-db
Technical documentationgithub.com/­apache/­doris/­wikiiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.ehcache.org/­documentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.html
DeveloperApache Software Foundation, originally contributed from BaiduApache Software FoundationTerracotta Inc, owned by Software AGFairCom Corporation
Initial release2017201820091979
Current release1.2.2, February 20231.1.0, April 20233.10.0, March 2022V12, November 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoApache Version 2; commercial licenses availablecommercial infoRestricted, free version available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJavaANSI C, C++
Server operating systemsLinuxAll OS with a Java VM (>= 1.8)All OS with a Java VMAIX
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,
Typing infopredefined data types such as float or dateyesyesyesyes, ANSI SQL Types, JSON, typed binary structures
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 indexesyesyesnoyes
SQL infoSupport of SQLyesSQL-like query languagenoyes, ANSI SQL with proprietary extensions
APIs and other access methodsJDBC
MySQL client
JDBC
Native API
JCacheADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
Supported programming languagesJavaC
C#
C++
Go
Java
Python
Scala
Java.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
Server-side scripts infoStored proceduresuser defined functionsyesnoyes info.Net, JavaScript, C/C++
Triggersnoyesyes infoCache Event Listenersyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioninghorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infoby using Terracotta ServerFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyes infoby using Terracotta Serveryes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoIntegration with Hadoop and Sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Tunable Consistency (Strong, Eventual, Weak)Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyes infosupports JTA and can work as an XA resourcetunable from ACID to Eventually Consistent
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infousing a tiered cache-storage approachYes, tunable from durable to delayed durability to in-memory
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardyesnoFine grained access rights according to SQL-standard with additional protections for files

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More resources
Apache DorisApache IoTDBEhcacheFaircom DB infoformerly c-treeACE
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