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DBMS > Apache IoTDB vs. Firebase Realtime Database vs. Hawkular Metrics vs. MarkLogic vs. TimescaleDB

System Properties Comparison Apache IoTDB vs. Firebase Realtime Database vs. Hawkular Metrics vs. MarkLogic vs. TimescaleDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonMarkLogic  Xexclude from comparisonTimescaleDB  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.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Operational and transactional Enterprise NoSQL databaseA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelTime Series DBMSDocument storeTime Series DBMSDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Time Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score14.29
Rank#39  Overall
#6  Document stores
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websiteiotdb.apache.orgfirebase.google.com/­products/­realtime-databasewww.hawkular.orgwww.marklogic.comwww.timescale.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlfirebase.google.com/­docs/­databasewww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.marklogic.comdocs.timescale.com
DeveloperApache Software FoundationGoogle infoacquired by Google 2014Community supported by Red HatMarkLogic Corp.Timescale
Initial release20182012201420012017
Current release1.1.0, April 202311.0, December 20222.13.0, November 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0commercial inforestricted free version is availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++C
Server operating systemsAll OS with a Java VM (>= 1.8)hostedLinux
OS X
Windows
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyesschema-freeschema-freeschema-free infoSchema can be enforcedyes
Typing infopredefined data types such as float or dateyesyesyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nononoyesyes
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLSQL-like query languagenonoyes infoSQL92yes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
Native API
Android
iOS
JavaScript API
RESTful HTTP API
HTTP RESTJava API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Java
JavaScript
Objective-C
Go
Java
Python
Ruby
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyeslimited functionality with using 'rules'noyes infovia XQuery or JavaScriptuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
TriggersyesCallbacks are triggered when data changesyes infovia Hawkular Alertingyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infobased on CassandraShardingyes, across time and space (hash partitioning) attributes
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 factor infobased on CassandrayesSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsno
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
Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnoACID 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.yesnoyes, with Range Indexesno
User concepts infoAccess controlyesyes, based on authentication and database rulesnoRole-based access control at the document and subdocument levelsfine grained access rights according to SQL-standard

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More resources
Apache IoTDBFirebase Realtime DatabaseHawkular MetricsMarkLogicTimescaleDB
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