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DBMS > Hawkular Metrics vs. MarkLogic vs. Spark SQL vs. Sphinx vs. Splice Machine

System Properties Comparison Hawkular Metrics vs. MarkLogic vs. Spark SQL vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameHawkular Metrics  Xexclude from comparisonMarkLogic  Xexclude from comparisonSpark SQL  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.Operational and transactional Enterprise NoSQL databaseSpark SQL is a component on top of 'Spark Core' for structured data processingOpen 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 DBMSDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMSSearch engineRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitewww.hawkular.orgwww.progress.com/­marklogicspark.apache.org/­sqlsphinxsearch.comsplicemachine.com
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidewww.progress.com/­marklogic/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperCommunity supported by Red HatMarkLogic Corp.Apache Software FoundationSphinx Technologies Inc.Splice Machine
Initial release20142001201420012014
Current release11.0, December 20223.5.0 ( 2.13), September 20233.5.1, February 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial inforestricted free version is availableOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++ScalaC++Java
Server operating systemsLinux
OS X
Windows
Linux
OS X
Windows
Linux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeschema-free infoSchema can be enforcedyesyesyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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.noyesno
Secondary indexesnoyesnoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoyes infoSQL92SQL-like DML and DDL statementsSQL-like query language (SphinxQL)yes
APIs and other access methodsHTTP RESTJava API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
JDBC
ODBC
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Java
Python
Ruby
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Python
R
Scala
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 proceduresnoyes infovia XQuery or JavaScriptnonoyes infoJava
Triggersyes infovia Hawkular Alertingyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraShardingyes, utilizing Spark CoreSharding 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 CassandrayesnonenoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsnoYes, 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 integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infocan act as a resource manager in an XA/JTA transactionnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes 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.noyes, with Range Indexesnoyes
User concepts infoAccess controlnoRole-based access control at the document and subdocument levelsnonoAccess rights for users, groups and roles according to SQL-standard

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Hawkular MetricsMarkLogicSpark SQLSphinxSplice Machine
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