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DBMS > GeoMesa vs. Solr vs. Sphinx vs. Splice Machine vs. Teradata Aster

System Properties Comparison GeoMesa vs. Solr vs. Sphinx vs. Splice Machine vs. Teradata Aster

Editorial information provided by DB-Engines
NameGeoMesa  Xexclude from comparisonSolr  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.A widely used distributed, scalable search engine based on Apache LuceneOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkPlatform for big data analytics on multistructured data sources and types
Primary database modelSpatial DBMSSearch engineSearch engineRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.86
Rank#205  Overall
#4  Spatial DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Score5.95
Rank#55  Overall
#5  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitewww.geomesa.orgsolr.apache.orgsphinxsearch.comsplicemachine.com
Technical documentationwww.geomesa.org/­documentation/­stable/­user/­index.htmlsolr.apache.org/­resources.htmlsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperCCRi and othersApache Software FoundationSphinx Technologies Inc.Splice MachineTeradata
Initial release20142006200120142005
Current release5.0.0, May 20249.6.1, May 20243.5.1, February 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache License 2.0Open Source infoApache Version 2Open Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScalaJavaC++Java
Server operating systemsAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Linux
Data schemeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyesyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesyes infosupports customizable data types and automatic typingnoyesyes
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.noyesyes infoin Aster File Store
Secondary indexesyesyes infoAll search fields are automatically indexedyes infofull-text index on all search fieldsyesyes
SQL infoSupport of SQLnoSolr Parallel SQL InterfaceSQL-like query language (SphinxQL)yesyes
APIs and other access methodsJava API
RESTful HTTP/JSON API
Proprietary protocolJDBC
Native Spark Datasource
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languages.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnoJava pluginsnoyes infoJavaR packages
Triggersnoyes infoUser configurable commands triggered on index changesnoyesno
Partitioning methods infoMethods for storing different data on different nodesdepending on storage layerShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar PartitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesdepending on storage layeryesnoneMulti-source replication
Source-replica replication
yes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reducenoYes, via Full Spark Integrationyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemdepending on storage layerEventual ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.depending on storage layeryesyesno
User concepts infoAccess controlyes infodepending on the DBMS used for storageyesnoAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard

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More resources
GeoMesaSolrSphinxSplice MachineTeradata Aster
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