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

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

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonDrizzle  Xexclude from comparisonKinetica  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 CPUsOpen-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 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
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitebangdb.comwww.kinetica.comsplicemachine.com
Technical documentationdocs.bangdb.comdocs.kinetica.comsplicemachine.com/­how-it-works
DeveloperSachin Sinha, BangDBDrizzle project, originally started by Brian AkerKineticaSplice Machine
Initial release2012200820122014
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 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++C++C, C++Java
Server operating systemsLinuxFreeBSD
Linux
OS X
LinuxLinux
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.nono
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesyesyes
SQL infoSupport of SQLSQL like support with command line toolyes infowith proprietary extensionsSQL-like DML and DDL statementsyes
APIs and other access methodsProprietary protocol
RESTful HTTP API
JDBCJDBC
ODBC
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C#
C++
Java
Python
C
C++
Java
PHP
C++
Java
JavaScript (Node.js)
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonouser defined functionsyes 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 rangeyes
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)Multi-source replication
Source-replica replication
Source-replica replicationMulti-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 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
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 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 levelAccess rights for users, groups and roles according to SQL-standard

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More resources
BangdbDrizzleKineticaSplice Machine
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