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DBMS > Bangdb vs. Citus vs. Drizzle vs. Splice Machine

System Properties Comparison Bangdb vs. Citus vs. Drizzle vs. Splice Machine

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonCitus  Xexclude from comparisonDrizzle  Xexclude from comparisonSplice Machine  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionConverged and high performance database for device data, events, time series, document and graphScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Open-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 DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#338  Overall
#47  Document stores
#32  Graph DBMS
#31  Time Series DBMS
Score2.15
Rank#117  Overall
#56  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitebangdb.comwww.citusdata.comsplicemachine.com
Technical documentationdocs.bangdb.comdocs.citusdata.comsplicemachine.com/­how-it-works
DeveloperSachin Sinha, BangDBDrizzle project, originally started by Brian AkerSplice Machine
Initial release2012201020082014
Current releaseBangDB 2.0, October 20218.1, December 20187.2.4, September 20123.1, March 2021
License infoCommercial or Open SourceOpen Source infoBSD 3Open Source infoAGPL, commercial license also availableOpen Source infoGNU GPLOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++CC++Java
Server operating systemsLinuxLinuxFreeBSD
Linux
OS X
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyesyesyes
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 infospecific XML type available, but no XML query functionality
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesyesyes
SQL infoSupport of SQLSQL like support with command line toolyes infostandard, with numerous extensionsyes infowith proprietary extensionsyes
APIs and other access methodsProprietary protocol
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBCJDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C#
C++
Java
Python
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C++
Java
PHP
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.noyes infoJava
Triggersyes, Notifications (with Streaming only)yesno infohooks for callbacks inside the server can be used.yes
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)Source-replica replication infoother methods possible by using 3rd party extensionsMulti-source replication
Source-replica replication
Multi-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 integritynoyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyesyesyes
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 modenoyes
User concepts infoAccess controlyes (enterprise version only)fine grained access rights according to SQL-standardPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles according to SQL-standard

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BangdbCitusDrizzleSplice Machine
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