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DBMS > Hawkular Metrics vs. PostgreSQL vs. Sphinx vs. Splice Machine

System Properties Comparison Hawkular Metrics vs. PostgreSQL vs. Sphinx vs. Splice Machine

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Editorial information provided by DB-Engines
NameHawkular Metrics  Xexclude from comparisonPostgreSQL  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Widely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelTime Series DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Search engineRelational DBMS
Secondary database modelsDocument store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score645.54
Rank#4  Overall
#4  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.hawkular.orgwww.postgresql.orgsphinxsearch.comsplicemachine.com
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidewww.postgresql.org/­docssphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperCommunity supported by Red HatPostgreSQL Global Development Group infowww.postgresql.org/­developerSphinx Technologies Inc.Splice Machine
Initial release20141989 info1989: Postgres, 1996: PostgreSQL20012014
Current release16.2, February 20243.5.1, February 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoBSDOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
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.
Aiven for PostgreSQL: Fully managed PostgreSQL for developers with 70+ extensions and flexible orchestration tools.
Implementation languageJavaCC++Java
Server operating systemsLinux
OS X
Windows
FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.noyes infospecific XML-type available, but no XML query functionality.
Secondary indexesnoyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoyes infostandard with numerous extensionsSQL-like query language (SphinxQL)yes
APIs and other access methodsHTTP RESTADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Java
Python
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.noyes infoJava
Triggersyes infovia Hawkular Alertingyesnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on Cassandrapartitioning by range, list and (since PostgreSQL 11) by hashSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on CassandraSource-replica replication infoother methods possible by using 3rd party extensionsnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlnofine grained access rights according to SQL-standardnoAccess rights for users, groups and roles according to SQL-standard

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Hawkular MetricsPostgreSQLSphinxSplice Machine
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