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DBMS > Hyprcubd vs. Linter vs. Sphinx vs. Splice Machine

System Properties Comparison Hyprcubd vs. Linter vs. Sphinx vs. Splice Machine

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Editorial information provided by DB-Engines
NameHyprcubd  Xexclude from comparisonLinter  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionServerless Time Series DBMSRDBMS for high security requirementsOpen 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 modelTime Series DBMSRelational DBMSSearch engineRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#335  Overall
#31  Time Series DBMS
Score0.12
Rank#293  Overall
#131  Relational DBMS
Score6.43
Rank#60  Overall
#7  Search engines
Score0.88
Rank#181  Overall
#92  Relational DBMS
Websitehyprcubd.comlinter.ru/­ensphinxsearch.comsplicemachine.com
Technical documentationsphinxsearch.com/­docsdoc.splicemachine.com
DeveloperHyprcubd, Inc.relex.ru/­enSphinx Technologies Inc.Splice Machine
Initial release199020012014
Current release3.3.1, July 20202.0
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 serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC and C++C++Java
Server operating systemshostedAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyes infotime, int, uint, float, stringyesnoyes
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.nono
Secondary indexesnoyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-like query languageyesSQL-like query language (SphinxQL)yes
APIs and other access methodsgRPC (https)ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
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 proceduresnoyes infoproprietary syntax with the possibility to convert from PL/SQLnoyes infoJava
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesnoneSharding 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 nodesSource-replica replicationnoneMulti-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 systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datanoyesyesyes, 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.noyes
User concepts infoAccess controltoken accessfine grained access rights according to SQL-standardnoAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
HyprcubdLinterSphinxSplice Machine
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
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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HyprcubdLinterSphinxSplice Machine
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