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DBMS > Apache IoTDB vs. FatDB vs. Hawkular Metrics vs. openGauss vs. TimescaleDB

System Properties Comparison Apache IoTDB vs. FatDB vs. Hawkular Metrics vs. openGauss vs. TimescaleDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonFatDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonopenGauss  Xexclude from comparisonTimescaleDB  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
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 .NET NoSQL DBMS that can integrate with and extend SQL Server.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by HuaweiA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelTime Series DBMSDocument store
Key-value store
Time Series DBMSRelational DBMSTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score1.08
Rank#183  Overall
#84  Relational DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websiteiotdb.apache.orgwww.hawkular.orggitee.com/­opengauss
opengauss.org
www.timescale.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.opengauss.org/­en
gitee.com/­opengauss/­docs
docs.timescale.com
DeveloperApache Software FoundationFatCloudCommunity supported by Red HatHuawei and openGauss communityTimescale
Initial release20182012201420192017
Current release1.1.0, April 20233.0, March 20222.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0Open SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC#JavaC, C++, JavaC
Server operating systemsAll OS with a Java VM (>= 1.8)WindowsLinux
OS X
Windows
LinuxLinux
OS X
Windows
Data schemeyesschema-freeschema-freeyesyes
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.nononoyes
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLSQL-like query languageno infoVia inetgration in SQL ServernoANSI SQL 2011yes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
Native API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
HTTP RESTJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#Go
Java
Python
Ruby
C
C++
Java
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyesyes infovia applicationsnoyesuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyesyes infovia applicationsyes infovia Hawkular Alertingyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding infobased on Cassandrahorizontal partitioning (by range, list and hash)yes, 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 factorselectable replication factor infobased on CassandraSource-replica replicationSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Immediate Consistency
Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACIDACID
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.yesnonono
User concepts infoAccess controlyesno infoCan implement custom security layer via applicationsnoAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Apache IoTDBFatDBHawkular MetricsopenGaussTimescaleDB
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