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DBMS > Apache IoTDB vs. Apache Phoenix vs. Hawkular Metrics vs. TimescaleDB vs. XTDB

System Properties Comparison Apache IoTDB vs. Apache Phoenix vs. Hawkular Metrics vs. TimescaleDB vs. XTDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonApache Phoenix  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonTimescaleDB  Xexclude from comparisonXTDB infoformerly named Crux  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 FlinkA scale-out RDBMS with evolutionary schema built on Apache HBaseHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelTime Series DBMSRelational DBMSTime Series DBMSTime Series DBMSDocument store
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
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Score0.11
Rank#343  Overall
#46  Document stores
Websiteiotdb.apache.orgphoenix.apache.orgwww.hawkular.orgwww.timescale.comgithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlphoenix.apache.orgwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.timescale.comwww.xtdb.com/­docs
DeveloperApache Software FoundationApache Software FoundationCommunity supported by Red HatTimescaleJuxt Ltd.
Initial release20182014201420172019
Current release1.1.0, April 20235.0-HBase2, July 2018 and 4.15-HBase1, December 20192.13.0, November 20231.19, September 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoApache 2.0Open Source infoMIT License
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJavaCClojure
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
Unix
Windows
Linux
OS X
Windows
Linux
OS X
Windows
All OS with a Java 8 (and higher) VM
Linux
Data schemeyesyes infolate-bound, schema-on-read capabilitiesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyes, extensible-data-notation format
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.nononoyesno
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLSQL-like query languageyesnoyes infofull PostgreSQL SQL syntaxlimited SQL, making use of Apache Calcite
APIs and other access methodsJDBC
Native API
JDBCHTTP RESTADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP REST
JDBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Go
Java
Python
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Clojure
Java
Server-side scripts infoStored proceduresyesuser defined functionsnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellno
Triggersyesnoyes infovia Hawkular Alertingyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding infobased on Cassandrayes, across time and space (hash partitioning) attributesnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replication
Source-replica replication
selectable replication factor infobased on CassandraSource-replica replication with hot standby and reads on replicas infoyes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparkHadoop integrationnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnono
User concepts infoAccess controlyesAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynofine grained access rights according to SQL-standard

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More resources
Apache IoTDBApache PhoenixHawkular MetricsTimescaleDBXTDB infoformerly named Crux
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