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DBMS > Sphinx vs. Splice Machine vs. Tibero

System Properties Comparison Sphinx vs. Splice Machine vs. Tibero

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Editorial information provided by DB-Engines
NameSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparisonTibero  Xexclude from comparison
DescriptionOpen 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 SparkA secure RDBMS, designed for easy portability from Oracle
Primary database modelSearch engineRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score6.56
Rank#57  Overall
#6  Search engines
Score0.74
Rank#196  Overall
#99  Relational DBMS
Score1.88
Rank#124  Overall
#62  Relational DBMS
Websitesphinxsearch.comsplicemachine.comwww.tmaxsoft.com/­products/­tibero
Technical documentationsphinxsearch.com/­docsdoc.splicemachine.comtechnet.tmaxsoft.com/­upload/­download/­online/­tibero/­pver-20150504-000002/­index.html
DeveloperSphinx Technologies Inc.Splice MachineTmaxSoft
Initial release200120142003
Current release3.3.1, July 20202.06, April 2015
License infoCommercial or Open SourceOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC and Assembler
Server operating systemsFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
AIX
HP-UX
Linux
Solaris
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or datenoyesyes
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
Secondary indexesyes infofull-text index on all search fieldsyesyes
SQL infoSupport of SQLSQL-like query language (SphinxQL)yesyes
APIs and other access methodsProprietary protocolJDBC
Native Spark Datasource
ODBC
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI
Supported programming languagesC++ 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++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic
Server-side scripts infoStored proceduresnoyes infoJavaPersistent Stored Procedure (PSM)
Triggersnoyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioninghorizontal partitioning infoby range, hash, list or composite
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyes 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.yesno infoplanned for next version
User concepts infoAccess controlnoAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard (SQL 92, SQL 99)
More information provided by the system vendor
SphinxSplice MachineTibero
Specific characteristicsTHE ONLY SCALE-OUT SQL RDBMS WITH BUILT-IN MACHINE LEARNING For data-rich, real-time...
» more
Competitive advantagesOperational Workloads: Full ACID support with high performance at scale Multi-row...
» more
Typical application scenariosNew AI/ML and IoT Applications Data Warehouse Offloads Application Modernization...
» more
Licensing and pricing modelsKubernetes Community Edition: https://hub.helm.sh/charts/splicemachine/splice-helm...
» more
News

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25 February 2021

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12 February 2021

Go Hands-On with Splice Machine’s Feature Store
12 February 2021

Three Ways to Talk Machine Learning with Splice Machine in January
6 January 2021

How To Get Real-Time Analytics By Consolidating Databases
21 May 2020

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
SphinxSplice MachineTibero
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