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DBMS > Hawkular Metrics vs. Hive vs. IRONdb vs. Microsoft Access vs. RDF4J

System Properties Comparison Hawkular Metrics vs. Hive vs. IRONdb vs. Microsoft Access vs. RDF4J

Editorial information provided by DB-Engines
NameHawkular Metrics  Xexclude from comparisonHive  Xexclude from comparisonIRONdb  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.data warehouse software for querying and managing large distributed datasets, built on HadoopA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelTime Series DBMSRelational DBMSTime Series DBMSRelational DBMSRDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.04
Rank#374  Overall
#38  Time Series DBMS
Score62.59
Rank#18  Overall
#12  Relational DBMS
Score105.40
Rank#11  Overall
#8  Relational DBMS
Score0.71
Rank#231  Overall
#9  RDF stores
Websitewww.hawkular.orghive.apache.orgwww.circonus.com/solutions/time-series-database/www.microsoft.com/­en-us/­microsoft-365/­accessrdf4j.org
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidecwiki.apache.org/­confluence/­display/­Hive/­Homedocs.circonus.com/irondb/category/getting-starteddeveloper.microsoft.com/­en-us/­accessrdf4j.org/­documentation
DeveloperCommunity supported by Red HatApache Software Foundation infoinitially developed by FacebookCirconus LLC.MicrosoftSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release20142012201719922004
Current release3.1.3, April 2022V0.10.20, January 20181902 (16.0.11328.20222), March 2019
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2commercialcommercial infoBundled with Microsoft OfficeOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC and C++C++Java
Server operating systemsLinux
OS X
Windows
All OS with a Java VMLinuxWindows infoNot a real database server, but making use of DLLsLinux
OS X
Unix
Windows
Data schemeschema-freeyesschema-freeyesyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyesyes infotext, numeric, histogramsyesyes
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.nono
Secondary indexesnoyesnoyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsSQL-like query language (Circonus Analytics Query Language: CAQL)yes infobut not compliant to any SQL standardno
APIs and other access methodsHTTP RESTJDBC
ODBC
Thrift
HTTP APIADO.NET
DAO
ODBC
OLE DB
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesGo
Java
Python
Ruby
C++
Java
PHP
Python
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Java
PHP
Python
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceyes, in Luayes infosince Access 2010 using the ACE-engineyes
Triggersyes infovia Hawkular Alertingnonoyes infosince Access 2010 using the ACE-engineyes
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraShardingAutomatic, metric affinity per nodenonenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on Cassandraselectable replication factorconfigurable replication factor, datacenter awarenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual ConsistencyImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID infobut no files for transaction loggingACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infobut no files for transaction loggingyes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlnoAccess rights for users, groups and rolesnono infoa simple user-level security was built in till version Access 2003no

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More resources
Hawkular MetricsHiveIRONdbMicrosoft AccessRDF4J infoformerly known as Sesame
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