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DBMS > eXtremeDB vs. IBM Db2 warehouse vs. Sphinx vs. Splice Machine

System Properties Comparison eXtremeDB vs. IBM Db2 warehouse vs. Sphinx vs. Splice Machine

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Editorial information provided by DB-Engines
NameeXtremeDB  Xexclude from comparisonIBM Db2 warehouse infoformerly named IBM dashDB  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionNatively in-memory DBMS with options for persistency, high-availability and clusteringCloud-based data warehousing serviceOpen 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
Relational DBMSSearch engineRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.73
Rank#227  Overall
#104  Relational DBMS
#18  Time Series DBMS
Score1.34
Rank#166  Overall
#76  Relational DBMS
Score6.03
Rank#60  Overall
#6  Search engines
Score0.54
Rank#255  Overall
#116  Relational DBMS
Websitewww.mcobject.comwww.ibm.com/­products/­db2/­warehousesphinxsearch.comsplicemachine.com
Technical documentationwww.mcobject.com/­docs/­extremedb.htmsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperMcObjectIBMSphinx Technologies Inc.Splice Machine
Initial release2001201420012014
Current release8.2, 20213.5.1, February 20233.1, March 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++C++Java
Server operating systemsAIX
HP-UX
Linux
macOS
Solaris
Windows
hostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesnoyes
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 availableno infoImport/export of XML data possible
Secondary indexesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLyes infowith the option: eXtremeSQLyesSQL-like query language (SphinxQL)yes
APIs and other access methods.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
.NET Client API
JDBC
ODBC
OLE DB
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
C
C#
C++
Java
Lua
Python
Scala
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
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 proceduresyesPL/SQL, SQL PLnoyes infoJava
Triggersyes infoby defining eventsyesnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning / shardingShardingSharding 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
yesnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes 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.yesyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardnoAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
eXtremeDBIBM Db2 warehouse infoformerly named IBM dashDBSphinxSplice 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,...
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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...
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Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
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eXtremeDBIBM Db2 warehouse infoformerly named IBM dashDBSphinxSplice Machine
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