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DBMS > Apache IoTDB vs. Firebase Realtime Database vs. MarkLogic vs. PostGIS vs. Sadas Engine

System Properties Comparison Apache IoTDB vs. Firebase Realtime Database vs. MarkLogic vs. PostGIS vs. Sadas Engine

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonMarkLogic  Xexclude from comparisonPostGIS  Xexclude from comparisonSadas Engine  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 FlinkCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Operational and transactional Enterprise NoSQL databaseSpatial extension of PostgreSQLSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments
Primary database modelTime Series DBMSDocument storeDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Spatial DBMSRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score13.64
Rank#39  Overall
#6  Document stores
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Score21.72
Rank#29  Overall
#1  Spatial DBMS
Score0.07
Rank#373  Overall
#157  Relational DBMS
Websiteiotdb.apache.orgfirebase.google.com/­products/­realtime-databasewww.progress.com/­marklogicpostgis.netwww.sadasengine.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlfirebase.google.com/­docs/­databasewww.progress.com/­marklogic/­documentationpostgis.net/­documentationwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
DeveloperApache Software FoundationGoogle infoacquired by Google 2014MarkLogic Corp.SADAS s.r.l.
Initial release20182012200120052006
Current release1.1.0, April 202311.0, December 20223.4.2, February 20248.0
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial inforestricted free version is availableOpen Source infoGPL v2.0commercial infofree trial version available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++CC++
Server operating systemsAll OS with a Java VM (>= 1.8)hostedLinux
OS X
Windows
AIX
Linux
Windows
Data schemeyesschema-freeschema-free infoSchema can be enforcedyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nonoyesyesno
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like query languagenoyes infoSQL92yesyes
APIs and other access methodsJDBC
Native API
Android
iOS
JavaScript API
RESTful HTTP API
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
JDBC
ODBC
Proprietary protocol
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Java
JavaScript
Objective-C
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C#
C++
Groovy
Java
PHP
Python
Server-side scripts infoStored proceduresyeslimited functionality with using 'rules'yes infovia XQuery or JavaScriptuser defined functionsno
TriggersyesCallbacks are triggered when data changesyesyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardingyes infobased on PostgreSQLhorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesyes infobased on PostgreSQLnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACID infocan act as a resource manager in an XA/JTA transactionACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes, with Range Indexesnoyes infomanaged by 'Learn by Usage'
User concepts infoAccess controlyesyes, based on authentication and database rulesRole-based access control at the document and subdocument levelsyes infobased on PostgreSQLAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache IoTDBFirebase Realtime DatabaseMarkLogicPostGISSadas Engine
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