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DBMS > Bangdb vs. Quasardb vs. Spark SQL vs. TimesTen

System Properties Comparison Bangdb vs. Quasardb vs. Spark SQL vs. TimesTen

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonQuasardb  Xexclude from comparisonSpark SQL  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphDistributed, high-performance timeseries databaseSpark SQL is a component on top of 'Spark Core' for structured data processingIn-Memory RDBMS compatible to Oracle
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Time Series DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.08
Rank#347  Overall
#47  Document stores
#34  Graph DBMS
#31  Time Series DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score1.31
Rank#163  Overall
#74  Relational DBMS
Websitebangdb.comquasar.aispark.apache.org/­sqlwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationdocs.bangdb.comdoc.quasar.ai/­masterspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.oracle.com/­database/­timesten-18.1
DeveloperSachin Sinha, BangDBquasardbApache Software FoundationOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release2012200920141998
Current releaseBangDB 2.0, October 20213.14.1, January 20243.5.0 ( 2.13), September 202311 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourceOpen Source infoBSD 3commercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoApache 2.0commercial
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++Scala
Server operating systemsLinuxBSD
Linux
OS X
Windows
Linux
OS X
Windows
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyes infointeger and binaryyesyes
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.nononono
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyes infowith tagsnoyes
SQL infoSupport of SQLSQL like support with command line toolSQL-like query languageSQL-like DML and DDL statementsyes
APIs and other access methodsProprietary protocol
RESTful HTTP API
HTTP APIJDBC
ODBC
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesC
C#
C++
Java
Python
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Java
Python
R
Scala
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresnononoPL/SQL
Triggersyes, Notifications (with Streaming only)nonono
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmSharding infoconsistent hashingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)Source-replica replication with selectable replication factornoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnowith Hadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyesyes
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyes infoby using LevelDByesyes infoby means of logfiles and checkpoints
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 infoTransient modenoyes
User concepts infoAccess controlyes (enterprise version only)Cryptographically strong user authentication and audit trailnofine grained access rights according to SQL-standard

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BangdbQuasardbSpark SQLTimesTen
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