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DBMS > Apache IoTDB vs. Badger vs. EJDB vs. Faircom DB vs. MaxDB

System Properties Comparison Apache IoTDB vs. Badger vs. EJDB vs. Faircom DB vs. MaxDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonBadger  Xexclude from comparisonEJDB  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonMaxDB infoformerly named Adabas-D  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 FlinkAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Embeddable document-store database library with JSON representation of queries (in MongoDB style)Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.A robust and reliable RDBMS optimized to run all major SAP solutions
Primary database modelTime Series DBMSKey-value storeDocument storeKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.14
Rank#331  Overall
#49  Key-value stores
Score0.27
Rank#297  Overall
#44  Document stores
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score2.32
Rank#112  Overall
#55  Relational DBMS
Websiteiotdb.apache.orggithub.com/­dgraph-io/­badgergithub.com/­Softmotions/­ejdbwww.faircom.com/­products/­faircom-dbmaxdb.sap.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlgodoc.org/­github.com/­dgraph-io/­badgergithub.com/­Softmotions/­ejdb/­blob/­master/­README.mddocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlmaxdb.sap.com/­documentation
DeveloperApache Software FoundationDGraph LabsSoftmotionsFairCom CorporationSAP, acquired from Software AG (Adabas-D) in 1997
Initial release20182017201219791984
Current release1.1.0, April 2023V12, November 20207.9.10.12, February 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoGPLv2commercial infoRestricted, free version availablecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaGoCANSI C, C++C++
Server operating systemsAll OS with a Java VM (>= 1.8)BSD
Linux
OS X
Solaris
Windows
server-lessAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
AIX
HP-UX
Linux
Solaris
Windows
Data schemeyesschema-freeschema-freeschema free, schema optional, schema required, partial schema,yes
Typing infopredefined data types such as float or dateyesnoyes infostring, integer, double, bool, date, object_idyes, ANSI SQL Types, JSON, typed binary structuresyes
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 indexesyesnonoyesyes
SQL infoSupport of SQLSQL-like query languagenonoyes, ANSI SQL with proprietary extensionsyes
APIs and other access methodsJDBC
Native API
in-process shared libraryADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
ADO.NET
JDBC
ODBC
WebDAV
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
GoActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
.Net
C#
Java
Perl
PHP
Python
Server-side scripts infoStored proceduresyesnonoyes info.Net, JavaScript, C/C++yes
Triggersyesnonoyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)nonenoneFile 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 replicasnonenoneyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).Source-replica replication
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
noneEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate Consistency
Foreign keys infoReferential integritynonono infotypically not needed, however similar functionality with collection joins possibleyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononotunable from ACID to Eventually ConsistentACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoRead/Write Lockingyesyes
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.yesnoyesno
User concepts infoAccess controlyesnonoFine grained access rights according to SQL-standard with additional protections for filesfine grained access rights according to SQL-standard

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More resources
Apache IoTDBBadgerEJDBFaircom DB infoformerly c-treeACEMaxDB infoformerly named Adabas-D
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