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DBMS > Hawkular Metrics vs. Manticore Search vs. MarkLogic vs. Splice Machine

System Properties Comparison Hawkular Metrics vs. Manticore Search vs. MarkLogic vs. Splice Machine

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Editorial information provided by DB-Engines
NameHawkular Metrics  Xexclude from comparisonManticore Search  Xexclude from comparisonMarkLogic  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.Multi-storage database for search, including full-text search.Operational and transactional Enterprise NoSQL databaseOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelTime Series DBMSSearch engineDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMS
Secondary database modelsTime Series DBMS infousing the Manticore Columnar Library
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score0.22
Rank#312  Overall
#21  Search engines
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.hawkular.orgmanticoresearch.comwww.marklogic.comsplicemachine.com
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidemanual.manticoresearch.comdocs.marklogic.comsplicemachine.com/­how-it-works
DeveloperCommunity supported by Red HatManticore SoftwareMarkLogic Corp.Splice Machine
Initial release2014201720012014
Current release6.0, February 202311.0, December 20223.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoGPL version 2commercial inforestricted free version is 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

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Implementation languageJavaC++C++Java
Server operating systemsLinux
OS X
Windows
FreeBSD
Linux
macOS
Windows
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeFixed schemaschema-free infoSchema can be enforcedyes
Typing infopredefined data types such as float or dateyesInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanyesyes
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.noCan index from XMLyes
Secondary indexesnoyes infofull-text index on all search fieldsyesyes
SQL infoSupport of SQLnoSQL-like query languageyes infoSQL92yes
APIs and other access methodsHTTP RESTBinary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Java 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
Native Spark Datasource
ODBC
Supported programming languagesGo
Java
Python
Ruby
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functionsyes infovia XQuery or JavaScriptyes infoJava
Triggersyes infovia Hawkular Alertingnoyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraSharding infoPartitioning is done manually, search queries against distributed index is supportedShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on CassandraSynchronous replication based on Galera libraryyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsYes, 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 integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyes infoisolated transactions for atomic changes and binary logging for safe writesACID infocan act as a resource manager in an XA/JTA transactionACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes infoThe original contents of fields are not stored in the Manticore index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes, with Range Indexesyes
User concepts infoAccess controlnonoRole-based access control at the document and subdocument levelsAccess rights for users, groups and roles according to SQL-standard

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More resources
Hawkular MetricsManticore SearchMarkLogicSplice Machine
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