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DBMS > Google Cloud Bigtable vs. Hawkular Metrics vs. Hive vs. IRONdb vs. RDF4J

System Properties Comparison Google Cloud Bigtable vs. Hawkular Metrics vs. Hive vs. IRONdb vs. RDF4J

Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonHive  Xexclude from comparisonIRONdb  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Hawkular 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 simplicityRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelKey-value store
Wide column store
Time Series DBMSRelational DBMSTime Series DBMSRDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Websitecloud.google.com/­bigtablewww.hawkular.orghive.apache.orgwww.circonus.com/solutions/time-series-database/rdf4j.org
Technical documentationcloud.google.com/­bigtable/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidecwiki.apache.org/­confluence/­display/­Hive/­Homedocs.circonus.com/irondb/category/getting-startedrdf4j.org/­documentation
DeveloperGoogleCommunity supported by Red HatApache Software Foundation infoinitially developed by FacebookCirconus LLC.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release20152014201220172004
Current release3.1.3, April 2022V0.10.20, January 2018
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache Version 2commercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC and C++Java
Server operating systemshostedLinux
OS X
Windows
All OS with a Java VMLinuxLinux
OS X
Unix
Windows
Data schemeschema-freeschema-freeyesschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or datenoyesyesyes infotext, numeric, histogramsyes
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.nonono
Secondary indexesnonoyesnoyes
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsSQL-like query language (Circonus Analytics Query Language: CAQL)no
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP RESTJDBC
ODBC
Thrift
HTTP APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
Go
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
Java
PHP
Python
Server-side scripts infoStored proceduresnonoyes infouser defined functions and integration of map-reduceyes, in Luayes
Triggersnoyes infovia Hawkular Alertingnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraShardingAutomatic, metric affinity per nodenone
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesselectable replication factor infobased on Cassandraselectable replication factorconfigurable replication factor, datacenter awarenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual ConsistencyImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnononoACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes 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.nonono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noAccess rights for users, groups and rolesnono

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More resources
Google Cloud BigtableHawkular MetricsHiveIRONdbRDF4J infoformerly known as Sesame
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