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

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

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonKinetica  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 dataFully vectorized database across both GPUs and CPUsOpen-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
Relational DBMSRelational DBMSKey-value store
Secondary database modelsSpatial DBMS
Time Series DBMS
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
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score0.00
Rank#382  Overall
#59  Key-value stores
Websitedruid.apache.orgwww.kinetica.comsplicemachine.comswaydb.simer.au
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.kinetica.comsplicemachine.com/­how-it-works
DeveloperApache Software Foundation and contributorsKineticaSplice MachineSimer Plaha
Initial release2012201220142018
Current release29.0.1, April 20247.1, August 20213.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen 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, C++JavaScala
Server operating systemsLinux
OS X
Unix
LinuxLinux
OS X
Solaris
Windows
Data schemeyes infoschema-less columns are supportedyesyesschema-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.nonono
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL for queryingSQL-like DML and DDL statementsyesno
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Java
Kotlin
Scala
Server-side scripts infoStored proceduresnouser defined functionsyes infoJavano
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyesno
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 enginesSource-replica replicationMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDAtomic 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 infoGPU vRAM or System RAMyesyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users and roles on table levelAccess rights for users, groups and roles according to SQL-standardno

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More resources
Apache DruidKineticaSplice MachineSwayDB
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