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DBMS > Bangdb vs. Spark SQL vs. Splice Machine vs. SQream DB

System Properties Comparison Bangdb vs. Spark SQL vs. Splice Machine vs. SQream DB

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonSpark SQL  Xexclude from comparisonSplice Machine  Xexclude from comparisonSQream DB  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphSpark SQL is a component on top of 'Spark Core' for structured data processingOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Sparka GPU-based, columnar RDBMS for big data analytics workloads
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Relational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial 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
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score0.74
Rank#224  Overall
#103  Relational DBMS
Websitebangdb.comspark.apache.org/­sqlsplicemachine.comsqream.com
Technical documentationdocs.bangdb.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsplicemachine.com/­how-it-worksdocs.sqream.com
DeveloperSachin Sinha, BangDBApache Software FoundationSplice MachineSQream Technologies
Initial release2012201420142017
Current releaseBangDB 2.0, October 20213.5.0 ( 2.13), September 20233.1, March 20212022.1.6, December 2022
License infoCommercial or Open SourceOpen Source infoBSD 3Open Source infoApache 2.0Open Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++ScalaJavaC++, CUDA, Haskell, Java, Scala
Server operating systemsLinuxLinux
OS X
Windows
Linux
OS X
Solaris
Windows
Linux
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyesyesyes, ANSI Standard SQL Types
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, geospatialnoyesno
SQL infoSupport of SQLSQL like support with command line toolSQL-like DML and DDL statementsyesyes
APIs and other access methodsProprietary protocol
RESTful HTTP API
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
.Net
JDBC
ODBC
Supported programming languagesC
C#
C++
Java
Python
Java
Python
R
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnonoyes infoJavauser defined functions in Python
Triggersyes, Notifications (with Streaming only)noyesno
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmyes, utilizing Spark CoreShared Nothhing Auto-Sharding, Columnar Partitioninghorizontal and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)noneMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyes, multi-version concurrency control (MVCC)yes
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)noAccess rights for users, groups and roles according to SQL-standard

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More resources
BangdbSpark SQLSplice MachineSQream DB
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