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DBMS > Hyprcubd vs. Oracle Berkeley DB vs. Oracle Rdb vs. Sphinx vs. Splice Machine

System Properties Comparison Hyprcubd vs. Oracle Berkeley DB vs. Oracle Rdb vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameHyprcubd  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonOracle Rdb  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.
DescriptionServerless Time Series DBMSWidely used in-process key-value storeOpen 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 DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSSearch engineRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score1.08
Rank#184  Overall
#85  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitehyprcubd.com (offline)www.oracle.com/­database/­technologies/­related/­berkeleydb.htmlwww.oracle.com/­database/­technologies/­related/­rdb.htmlsphinxsearch.comsplicemachine.com
Technical documentationdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlwww.oracle.com/­database/­technologies/­related/­rdb-doc.htmlsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperHyprcubd, Inc.Oracle infooriginally developed by Sleepycat, which was acquired by OracleOracle, originally developed by Digital Equipment Corporation (DEC)Sphinx Technologies Inc.Splice Machine
Initial release1994198420012014
Current release18.1.40, May 20207.4.1.1, 20213.5.1, February 20233.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infocommercial license availablecommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC, Java, C++ (depending on the Berkeley DB edition)C++Java
Server operating systemshostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
HP Open VMSFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyes infotime, int, uint, float, stringnoyesnoyes
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.noyes infoonly with the Berkeley DB XML editionno
Secondary indexesnoyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-like query languageyes infoSQL interfaced based on SQLite is availableyesSQL-like query language (SphinxQL)yes
APIs and other access methodsgRPC (https)Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languages.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
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 proceduresnononoyes infoJava
Triggersnoyes infoonly for the SQL APInoyes
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 methodsnonononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDyes, on a single nodenoACID
Concurrency infoSupport for concurrent manipulation of datanoyesyesyes, 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.noyesnoyes
User concepts infoAccess controltoken accessnonoAccess rights for users, groups and roles according to SQL-standard

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More resources
HyprcubdOracle Berkeley DBOracle RdbSphinxSplice Machine
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