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DBMS > Hawkular Metrics vs. Hive vs. Neo4j vs. Netezza

System Properties Comparison Hawkular Metrics vs. Hive vs. Neo4j vs. Netezza

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Editorial information provided by DB-Engines
NameHawkular Metrics  Xexclude from comparisonHive  Xexclude from comparisonNeo4j  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
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 HadoopScalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offeringsData warehouse and analytics appliance part of IBM PureSystems
Primary database modelTime Series DBMSRelational DBMSGraph DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score44.89
Rank#21  Overall
#1  Graph DBMS
Score8.59
Rank#45  Overall
#29  Relational DBMS
Websitewww.hawkular.orghive.apache.orgneo4j.comwww.ibm.com/­products/­netezza
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidecwiki.apache.org/­confluence/­display/­Hive/­Homeneo4j.com/­docs
DeveloperCommunity supported by Red HatApache Software Foundation infoinitially developed by FacebookNeo4j, Inc.IBM
Initial release2014201220072000
Current release3.1.3, April 20225.20, May 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2Open Source infoGPL version3, commercial licenses availablecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.
Implementation languageJavaJavaJava, Scala
Server operating systemsLinux
OS X
Windows
All OS with a Java VMLinux infoCan also be used server-less as embedded Java database.
OS X
Solaris
Windows
Linux infoincluded in appliance
Data schemeschema-freeyesschema-free and schema-optionalyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.no
Secondary indexesnoyesyes infopluggable indexing subsystem, by default Apache Luceneyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsnoyes
APIs and other access methodsHTTP RESTJDBC
ODBC
Thrift
Bolt protocol
Cypher query language
Java API
Neo4j-OGM infoObject Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3
JDBC
ODBC
OLE DB
Supported programming languagesGo
Java
Python
Ruby
C++
Java
PHP
Python
.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceyes infoUser defined Procedures and Functionsyes
Triggersyes infovia Hawkular Alertingnoyes infovia event handlerno
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraShardingyes using Neo4j FabricSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on Cassandraselectable replication factorCausal Clustering using Raft protocol infoavailable in in Enterprise Version onlySource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual ConsistencyCausal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode
Foreign keys infoReferential integritynonoyes infoRelationships in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlnoAccess rights for users, groups and rolesUsers, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)Users with fine-grained authorization concept
More information provided by the system vendor
Hawkular MetricsHiveNeo4jNetezza infoAlso called PureData System for Analytics by IBM
Specific characteristicsNeo4j delivers graph technology that has been battle tested for performance and scale...
» more
Competitive advantagesNeo4j is the market leader, graph database category creator, and the most widely...
» more
Typical application scenariosReal-Time Recommendations Master Data Management Identity and Access Management Network...
» more
Key customersOver 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
» more
Market metricsNeo4j boasts the world's largest graph database ecosystem with more than 140 million...
» more
Licensing and pricing modelsGPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
» more
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