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DBMS > Bangdb vs. Drizzle vs. Kinetica vs. RDF4J vs. Splice Machine

System Properties Comparison Bangdb vs. Drizzle vs. Kinetica vs. RDF4J vs. Splice Machine

Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonDrizzle  Xexclude from comparisonKinetica  Xexclude from comparisonRDF4J infoformerly known as Sesame  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 graphMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Fully vectorized database across both GPUs and CPUsRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.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 DBMSRDF storeRelational DBMS
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
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
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitebangdb.comwww.kinetica.comrdf4j.orgsplicemachine.com
Technical documentationdocs.bangdb.comdocs.kinetica.comrdf4j.org/­documentationsplicemachine.com/­how-it-works
DeveloperSachin Sinha, BangDBDrizzle project, originally started by Brian AkerKineticaSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Splice Machine
Initial release20122008201220042014
Current releaseBangDB 2.0, October 20217.2.4, September 20127.1, August 20213.1, March 2021
License infoCommercial or Open SourceOpen Source infoBSD 3Open Source infoGNU GPLcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++C++C, C++JavaJava
Server operating systemsLinuxFreeBSD
Linux
OS X
LinuxLinux
OS X
Unix
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesyesyes infoRDF Schemasyes
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyesyesyesyes
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, geospatialyesyesyesyes
SQL infoSupport of SQLSQL like support with command line toolyes infowith proprietary extensionsSQL-like DML and DDL statementsnoyes
APIs and other access methodsProprietary protocol
RESTful HTTP API
JDBCJDBC
ODBC
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C#
C++
Java
Python
C
C++
Java
PHP
C++
Java
JavaScript (Node.js)
Python
Java
PHP
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonouser defined functionsyesyes infoJava
Triggersyes, Notifications (with Streaming only)no infohooks for callbacks inside the server can be used.yes infotriggers when inserted values for one or more columns fall within a specified rangeyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingShardingnoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)Multi-source replication
Source-replica replication
Source-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 systemTunable consistency, set CAP knob accordinglyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyesyesyes infoin-memory storage is supported as wellyes
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 infoGPU vRAM or System RAMyes
User concepts infoAccess controlyes (enterprise version only)Pluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users and roles on table levelnoAccess rights for users, groups and roles according to SQL-standard

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More resources
BangdbDrizzleKineticaRDF4J infoformerly known as SesameSplice Machine
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