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DBMS > Apache Impala vs. MonetDB vs. Postgres-XL vs. Splice Machine vs. WakandaDB

System Properties Comparison Apache Impala vs. MonetDB vs. Postgres-XL vs. Splice Machine vs. WakandaDB

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonMonetDB  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSplice Machine  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA relational database management system that stores data in columnsBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMSObject oriented DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score1.72
Rank#141  Overall
#64  Relational DBMS
Score0.53
Rank#254  Overall
#117  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score0.10
Rank#356  Overall
#16  Object oriented DBMS
Websiteimpala.apache.orgwww.monetdb.orgwww.postgres-xl.orgsplicemachine.comwakanda.github.io
Technical documentationimpala.apache.org/­impala-docs.htmlwww.monetdb.org/­Documentationwww.postgres-xl.org/­documentationsplicemachine.com/­how-it-workswakanda.github.io/­doc
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaMonetDB BVSplice MachineWakanda SAS
Initial release201320042014 infosince 2012, originally named StormDB20142012
Current release4.1.0, June 2022Dec2023 (11.49), December 202310 R1, October 20183.1, March 20212.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoMozilla Public License 2.0Open Source infoMozilla public licenseOpen Source infoAGPL 3.0, commercial license availableOpen Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CCJavaC++, JavaScript
Server operating systemsLinuxFreeBSD
Linux
OS X
Solaris
Windows
Linux
macOS
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeyesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.noyes infoXML type, but no XML query functionalityno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infoSQL 2003 with some extensionsyes infodistributed, parallel query executionyesno
APIs and other access methodsJDBC
ODBC
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
Native Spark Datasource
ODBC
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCC
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
JavaScript
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes, in SQL, C, Ruser defined functionsyes infoJavayes
Triggersnoyesyesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding via remote tableshorizontal partitioningShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornone infoSource-replica replication available in experimental statusMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoMVCCACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standardyes

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More resources
Apache ImpalaMonetDBPostgres-XLSplice MachineWakandaDB
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