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DBMS > Apache Druid vs. MarkLogic vs. Splice Machine vs. SwayDB

System Properties Comparison Apache Druid vs. MarkLogic vs. Splice Machine vs. SwayDB

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonMarkLogic  Xexclude from comparisonSplice Machine  Xexclude from comparisonSwayDB  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataOperational and transactional Enterprise NoSQL databaseOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelRelational DBMS
Time Series DBMS
Document store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
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
Score0.00
Rank#382  Overall
#59  Key-value stores
Websitedruid.apache.orgwww.marklogic.comsplicemachine.comswaydb.simer.au
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.marklogic.comsplicemachine.com/­how-it-works
DeveloperApache Software Foundation and contributorsMarkLogic Corp.Splice MachineSimer Plaha
Initial release2012200120142018
Current release29.0.1, April 202411.0, December 20223.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache license v2commercial inforestricted free version is availableOpen Source infoAGPL 3.0, commercial license availableOpen Source infoGNU Affero GPL V3.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++JavaScala
Server operating systemsLinux
OS X
Unix
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeyes infoschema-less columns are supportedschema-free infoSchema can be enforcedyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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 indexesyesyesyesno
SQL infoSupport of SQLSQL for queryingyes infoSQL92yesno
APIs and other access methodsJDBC
RESTful HTTP/JSON API
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 languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Java
Kotlin
Scala
Server-side scripts infoStored proceduresnoyes infovia XQuery or JavaScriptyes infoJavano
Triggersnoyesyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyesMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infocan act as a resource manager in an XA/JTA transactionACIDAtomic execution of operations
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
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.noyes, with Range Indexesyesyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemRole-based access control at the document and subdocument levelsAccess rights for users, groups and roles according to SQL-standardno

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More resources
Apache DruidMarkLogicSplice MachineSwayDB
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