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DBMS > Bangdb vs. NuoDB vs. Sphinx vs. Splice Machine

System Properties Comparison Bangdb vs. NuoDB vs. Sphinx vs. Splice Machine

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonNuoDB  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphNuoDB is a webscale distributed database that supports SQL and ACID transactionsOpen 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 modelDocument store
Graph DBMS
Time Series DBMS
Relational DBMSSearch engineRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.07
Rank#346  Overall
#47  Document stores
#35  Graph DBMS
#32  Time Series DBMS
Score0.87
Rank#201  Overall
#94  Relational DBMS
Score5.97
Rank#56  Overall
#5  Search engines
Score0.54
Rank#244  Overall
#114  Relational DBMS
Websitebangdb.comwww.3ds.com/­nuodb-distributed-sql-databasesphinxsearch.comsplicemachine.com
Technical documentationdocs.bangdb.comdoc.nuodb.comsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperSachin Sinha, BangDBDassault Systèmes infooriginally NuoDB, Inc.Sphinx Technologies Inc.Splice Machine
Initial release2012201320012014
Current releaseBangDB 2.0, October 20213.5.1, February 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoBSD 3commercial infolimited edition freeOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++C++C++Java
Server operating systemsLinuxhosted infoAmazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyesnoyes
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 indexesyes infosecondary, composite, nested, reverse, geospatialyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL like support with command line toolyesSQL-like query language (SphinxQL)yes
APIs and other access methodsProprietary protocol
RESTful HTTP API
ADO.NET
JDBC
ODBC
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C#
C++
Java
Python
.Net
C
C++
Go
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
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 proceduresnoJava, SQLnoyes infoJava
Triggersyes, Notifications (with Streaming only)yesnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmdata is dynamically stored/cached on the nodes where it is read/writtenSharding 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 nodesselectable replication factor, Knob for CAP (enterprise version only)yes infoManaged transparently by NuoDBnoneMulti-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 systemTunable consistency, set CAP knob accordinglyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infotunable commit protocolnoACID
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyes infoMVCCyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyesyes 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.yes, run db with in-memory only modeyes infoTemporary tableyes
User concepts infoAccess controlyes (enterprise version only)Standard SQL roles/ privileges, Administrative UsersnoAccess rights for users, groups and roles according to SQL-standard

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BangdbNuoDBSphinxSplice Machine
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