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DBMS > Apache IoTDB vs. Apache Phoenix vs. Hawkular Metrics vs. IBM Db2 Event Store vs. openGauss

System Properties Comparison Apache IoTDB vs. Apache Phoenix vs. Hawkular Metrics vs. IBM Db2 Event Store vs. openGauss

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonApache Phoenix  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonopenGauss  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.Distributed Event Store optimized for Internet of Things use casesAn enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei
Primary database modelTime Series DBMSRelational DBMSTime Series DBMSEvent Store
Time Series DBMS
Relational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Score1.06
Rank#184  Overall
#84  Relational DBMS
Websiteiotdb.apache.orgphoenix.apache.orgwww.hawkular.orgwww.ibm.com/­products/­db2-event-storegitee.com/­opengauss
opengauss.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlphoenix.apache.orgwww.hawkular.org/­hawkular-metrics/­docs/­user-guidewww.ibm.com/­docs/­en/­db2-event-storedocs.opengauss.org/­en
gitee.com/­opengauss/­docs
DeveloperApache Software FoundationApache Software FoundationCommunity supported by Red HatIBMHuawei and openGauss community
Initial release20182014201420172019
Current release1.1.0, April 20235.0-HBase2, July 2018 and 4.15-HBase1, December 20192.03.0, March 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoApache 2.0commercial infofree developer edition availableOpen Source
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 languageJavaJavaJavaC and C++C, C++, Java
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
Unix
Windows
Linux
OS X
Windows
Linux infoLinux, macOS, Windows for the developer additionLinux
Data schemeyesyes infolate-bound, schema-on-read capabilitiesschema-freeyesyes
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.nonononono
Secondary indexesyesyesnonoyes
SQL infoSupport of SQLSQL-like query languageyesnoyes infothrough the embedded Spark runtimeANSI SQL 2011
APIs and other access methodsJDBC
Native API
JDBCHTTP RESTADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Go
Java
Python
Ruby
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
C
C++
Java
Server-side scripts infoStored proceduresyesuser defined functionsnoyesyes
Triggersyesnoyes infovia Hawkular Alertingnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding infobased on CassandraShardinghorizontal partitioning (by range, list and hash)
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 CassandraActive-active shard replicationSource-replica replication
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
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesNo - written data is immutableyes
Durability infoSupport for making data persistentyesyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyesno
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-standardAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache IoTDBApache PhoenixHawkular MetricsIBM Db2 Event StoreopenGauss
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