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DBMS > Apache Impala vs. Hawkular Metrics vs. MarkLogic vs. Splice Machine

System Properties Comparison Apache Impala vs. Hawkular Metrics vs. MarkLogic vs. Splice Machine

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonMarkLogic  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.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 modelRelational DBMSTime Series DBMSDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score0.01
Rank#377  Overall
#39  Time Series DBMS
Score4.15
Rank#70  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#8  Search engines
Score0.54
Rank#244  Overall
#114  Relational DBMS
Websiteimpala.apache.orgwww.hawkular.orgwww.progress.com/­marklogicsplicemachine.com
Technical documentationimpala.apache.org/­impala-docs.htmlwww.hawkular.org/­hawkular-metrics/­docs/­user-guidewww.progress.com/­marklogic/­documentationsplicemachine.com/­how-it-works
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaCommunity supported by Red HatMarkLogic Corp.Splice Machine
Initial release2013201420012014
Current release4.1.0, June 202211.0, December 20223.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0commercial 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 languageC++JavaC++Java
Server operating systemsLinuxLinux
OS X
Windows
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeschema-free infoSchema can be enforcedyes
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.nonoyes
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes infoSQL92yes
APIs and other access methodsJDBC
ODBC
HTTP 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
Native Spark Datasource
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCGo
Java
Python
Ruby
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyes infovia XQuery or JavaScriptyes infoJava
Triggersnoyes infovia Hawkular Alertingyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factor infobased on CassandrayesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyes 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 ConsistencyEventual 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 datanonoACID 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 persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes, with Range Indexesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoRole-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
Apache ImpalaHawkular MetricsMarkLogicSplice Machine
Conferences, events and webinars

Progress MarkLogic World
Washington DC, 23-25 September 2024

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