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DBMS > Apache Impala vs. Kinetica vs. Realm vs. Splice Machine

System Properties Comparison Apache Impala vs. Kinetica vs. Realm vs. Splice Machine

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonKinetica  Xexclude from comparisonRealm  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopFully vectorized database across both GPUs and CPUsA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSRelational DBMSDocument storeRelational DBMS
Secondary database modelsDocument storeSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score7.41
Rank#52  Overall
#8  Document stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteimpala.apache.orgwww.kinetica.comrealm.iosplicemachine.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.kinetica.comrealm.io/­docssplicemachine.com/­how-it-works
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaKineticaRealm, acquired by MongoDB in May 2019Splice Machine
Initial release2013201220142014
Current release4.1.0, June 20227.1, August 20213.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen SourceOpen 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++C, C++Java
Server operating systemsLinuxLinuxAndroid
Backend: server-less
iOS
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyesyesyes
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.nonono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like DML and DDL statementsnoyes
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC++
Java
JavaScript (Node.js)
Python
.Net
Java infowith Android only
Objective-C
React Native
Swift
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functionsno inforuns within the applications so server-side scripts are unnecessaryyes infoJava
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infoChange Listenersyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, 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.noyes infoGPU vRAM or System RAMyes infoIn-Memory realmyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users and roles on table levelyesAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache ImpalaKineticaRealmSplice Machine
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