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DBMS > Faircom DB vs. Hyprcubd vs. Sphinx vs. Splice Machine vs. ToroDB

System Properties Comparison Faircom DB vs. Hyprcubd vs. Sphinx vs. Splice Machine vs. ToroDB

Editorial information provided by DB-Engines
NameFaircom DB infoformerly c-treeACE  Xexclude from comparisonHyprcubd  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparisonToroDB  Xexclude from comparison
Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Serverless 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 SparkA MongoDB-compatible JSON document store, built on top of PostgreSQL
Primary database modelKey-value store
Relational DBMS
Time Series DBMSSearch engineRelational DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#304  Overall
#43  Key-value stores
#136  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitewww.faircom.com/­products/­faircom-dbhyprcubd.com (offline)sphinxsearch.comsplicemachine.comgithub.com/­torodb/­server
Technical documentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperFairCom CorporationHyprcubd, Inc.Sphinx Technologies Inc.Splice Machine8Kdata
Initial release1979200120142016
Current releaseV12, November 20203.5.1, February 20233.1, March 2021
License infoCommercial or Open Sourcecommercial infoRestricted, free version availablecommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license availableOpen Source infoAGPL-V3
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageANSI C, C++GoC++JavaJava
Server operating systemsAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
hostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
All OS with a Java 7 VM
Data schemeschema free, schema optional, schema required, partial schema,yesyesyesschema-free
Typing infopredefined data types such as float or dateyes, ANSI SQL Types, JSON, typed binary structuresyes infotime, int, uint, float, stringnoyesyes infostring, integer, double, boolean, date, object_id
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.nonono
Secondary indexesyesnoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLyes, ANSI SQL with proprietary extensionsSQL-like query languageSQL-like query language (SphinxQL)yes
APIs and other access methodsADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
gRPC (https)Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
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 proceduresyes info.Net, JavaScript, C/C++nonoyes infoJava
Triggersyesnonoyesno
Partitioning methods infoMethods for storing different data on different nodesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar PartitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).noneMulti-source replication
Source-replica 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 Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Eventual ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datatunable from ACID to Eventually ConsistentnonoACIDno
Concurrency infoSupport for concurrent manipulation of datayesnoyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentYes, tunable from durable to delayed durability to in-memoryyesyes 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.yesnoyes
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filestoken accessnoAccess rights for users, groups and roles according to SQL-standardAccess rights for users and roles

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More resources
Faircom DB infoformerly c-treeACEHyprcubdSphinxSplice MachineToroDB
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