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

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

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Editorial information provided by DB-Engines
NameHyprcubd  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparisonYanza  Xexclude from comparison
DescriptionServerless Time Series DBMSOpen 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 SparkTime Series DBMS for IoT Applications
Primary database modelTime Series DBMSSearch engineRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#335  Overall
#31  Time Series DBMS
Score6.43
Rank#60  Overall
#7  Search engines
Score0.88
Rank#181  Overall
#92  Relational DBMS
Score0.00
Rank#335  Overall
#31  Time Series DBMS
Websitehyprcubd.comsphinxsearch.comsplicemachine.comyanza.com
Technical documentationsphinxsearch.com/­docsdoc.splicemachine.com
DeveloperHyprcubd, Inc.Sphinx Technologies Inc.Splice MachineYanza
Initial release200120142015
Current release3.3.1, July 20202.0
License infoCommercial or Open SourcecommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license availablecommercial infofree version available
Cloud-based only infoOnly available as a cloud serviceyesnonono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++Java
Server operating systemshostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Windows
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyes infotime, int, uint, float, stringnoyesno
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 indexesnoyes infofull-text index on all search fieldsyesno
SQL infoSupport of SQLSQL-like query languageSQL-like query language (SphinxQL)yesno
APIs and other access methodsgRPC (https)Proprietary protocolJDBC
Native Spark Datasource
ODBC
HTTP API
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
any language that supports HTTP calls
Server-side scripts infoStored proceduresnonoyes infoJavano
Triggersnonoyesyes infoTimer and event based
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 Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDno
Concurrency infoSupport for concurrent manipulation of datanoyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyes 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.noyes
User concepts infoAccess controltoken accessnoAccess rights for users, groups and roles according to SQL-standardno
More information provided by the system vendor
HyprcubdSphinxSplice MachineYanza
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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