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DBMS > Apache IoTDB vs. Databend vs. Hawkular Metrics vs. MarkLogic vs. TimescaleDB

System Properties Comparison Apache IoTDB vs. Databend vs. Hawkular Metrics vs. MarkLogic vs. TimescaleDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDatabend  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 FlinkAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityHawkular 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 DBMSRelational DBMSTime 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
Score0.30
Rank#287  Overall
#130  Relational DBMS
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.orggithub.com/­datafuselabs/­databend
www.databend.com
www.hawkular.orgwww.marklogic.comwww.timescale.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.databend.comwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.marklogic.comdocs.timescale.com
DeveloperApache Software FoundationDatabend LabsCommunity supported by Red HatMarkLogic Corp.Timescale
Initial release20182021201420012017
Current release1.1.0, April 20231.0.59, April 202311.0, December 20222.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoApache 2.0commercial inforestricted free version is availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaRustJavaC++C
Server operating systemsAll OS with a Java VM (>= 1.8)hosted
Linux
macOS
Linux
OS X
Windows
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyesyesschema-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 indexesyesnonoyesyes
SQL infoSupport of SQLSQL-like query languageyesnoyes infoSQL92yes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
Native API
CLI Client
JDBC
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
Go
Java
JavaScript (Node.js)
Python
Rust
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 proceduresyesnonoyes 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
Triggersyesnoyes infovia Hawkular Alertingyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneSharding 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 replicasnoneselectable 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
Immediate ConsistencyEventual 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 controlyesUsers with fine-grained authorization concept, user rolesnoRole-based access control at the document and subdocument levelsfine grained access rights according to SQL-standard

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More resources
Apache IoTDBDatabendHawkular MetricsMarkLogicTimescaleDB
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