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DBMS > eXtremeDB vs. Microsoft Azure Table Storage vs. Solr vs. Sphinx vs. Splice Machine

System Properties Comparison eXtremeDB vs. Microsoft Azure Table Storage vs. Solr vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameeXtremeDB  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSolr  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionNatively in-memory DBMS with options for persistency, high-availability and clusteringA Wide Column Store for rapid development using massive semi-structured datasetsA 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 Spark
Primary database modelRelational DBMS
Time Series DBMS
Wide column storeSearch engineSearch engineRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.80
Rank#214  Overall
#99  Relational DBMS
#18  Time Series DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
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.mcobject.comazure.microsoft.com/­en-us/­services/­storage/­tablessolr.apache.orgsphinxsearch.comsplicemachine.com
Technical documentationwww.mcobject.com/­docs/­extremedb.htmsolr.apache.org/­resources.htmlsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperMcObjectMicrosoftApache Software FoundationSphinx Technologies Inc.Splice Machine
Initial release20012012200620012014
Current release8.2, 20219.6.1, May 20243.5.1, February 20233.1, March 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2Open Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++JavaC++Java
Server operating systemsAIX
HP-UX
Linux
macOS
Solaris
Windows
hostedAll 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
Data schemeyesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyesyes
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic typingnoyes
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.no infosupport of XML interfaces availablenoyes
Secondary indexesyesnoyes infoAll search fields are automatically indexedyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLyes infowith the option: eXtremeSQLnoSolr Parallel SQL InterfaceSQL-like query language (SphinxQL)yes
APIs and other access methods.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
RESTful HTTP APIJava API
RESTful HTTP/JSON API
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
C
C#
C++
Java
Lua
Python
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.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
Server-side scripts infoStored proceduresyesnoJava pluginsnoyes infoJava
Triggersyes infoby defining eventsnoyes infoUser configurable commands triggered on index changesnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning / shardingSharding infoImplicit feature of the cloud serviceShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesActive Replication Fabricâ„¢ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yesnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reducenoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDoptimistic lockingoptimistic lockingnoACID
Concurrency infoSupport for concurrent manipulation of datayes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyes
User concepts infoAccess controlAccess rights based on private key authentication or shared access signaturesyesnoAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
eXtremeDBMicrosoft Azure Table StorageSolrSphinxSplice Machine
Specific characteristicseXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more
Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more
Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
» more
Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
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eXtremeDBMicrosoft Azure Table StorageSolrSphinxSplice Machine
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