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DBMS > Postgres-XL vs. Solr vs. Splice Machine vs. WakandaDB

System Properties Comparison Postgres-XL vs. Solr vs. Splice Machine vs. WakandaDB

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Editorial information provided by DB-Engines
NamePostgres-XL  Xexclude from comparisonSolr  Xexclude from comparisonSplice Machine  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresA widely used distributed, scalable search engine based on Apache LuceneOpen-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 DBMSSearch engineRelational DBMSObject oriented DBMS
Secondary database modelsDocument store
Spatial DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.49
Rank#256  Overall
#117  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websitewww.postgres-xl.orgsolr.apache.orgsplicemachine.comwakanda.github.io
Technical documentationwww.postgres-xl.org/­documentationsolr.apache.org/­resources.htmlsplicemachine.com/­how-it-workswakanda.github.io/­doc
DeveloperApache Software FoundationSplice MachineWakanda SAS
Initial release2014 infosince 2012, originally named StormDB200620142012
Current release10 R1, October 20189.6.0, April 20243.1, March 20212.7.0 (AprilĀ 29, 2019), April 2019
License infoCommercial or Open SourceOpen Source infoMozilla public licenseOpen Source infoApache Version 2Open Source infoAGPL 3.0, commercial license availableOpen Source infoAGPLv3, extended 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 languageCJavaJavaC++, JavaScript
Server operating systemsLinux
macOS
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyesyes
Typing infopredefined data types such as float or dateyesyes infosupports customizable data types and automatic typingyesyes
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.yes infoXML type, but no XML query functionalityyesno
Secondary indexesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLyes infodistributed, parallel query executionSolr Parallel SQL Interfaceyesno
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Java API
RESTful HTTP/JSON API
JDBC
Native Spark Datasource
ODBC
RESTful HTTP API
Supported programming languages.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
JavaScript
Server-side scripts infoStored proceduresuser defined functionsJava pluginsyes infoJavayes
Triggersyesyes infoUser configurable commands triggered on index changesyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoMVCCoptimistic lockingACIDACID
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.noyesyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardyesAccess rights for users, groups and roles according to SQL-standardyes

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More resources
Postgres-XLSolrSplice MachineWakandaDB
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