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DBMS > Bangdb vs. Google Cloud Bigtable vs. MonetDB vs. Splice Machine

System Properties Comparison Bangdb vs. Google Cloud Bigtable vs. MonetDB vs. Splice Machine

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMonetDB  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A relational database management system that stores data in columnsOpen-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
Key-value store
Wide column store
Relational DBMSRelational DBMS
Secondary database modelsSpatial DBMSDocument store
Spatial 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
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score1.72
Rank#145  Overall
#67  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitebangdb.comcloud.google.com/­bigtablewww.monetdb.orgsplicemachine.com
Technical documentationdocs.bangdb.comcloud.google.com/­bigtable/­docswww.monetdb.org/­Documentationsplicemachine.com/­how-it-works
DeveloperSachin Sinha, BangDBGoogleMonetDB BVSplice Machine
Initial release2012201520042014
Current releaseBangDB 2.0, October 2021Dec2023 (11.49), December 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoBSD 3commercialOpen Source infoMozilla Public License 2.0Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++CJava
Server operating systemsLinuxhostedFreeBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsnoyesyes
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, geospatialnoyesyes
SQL infoSupport of SQLSQL like support with command line toolnoyes infoSQL 2003 with some extensionsyes
APIs and other access methodsProprietary protocol
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C#
C++
Java
Python
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonoyes, in SQL, C, Ryes infoJava
Triggersyes, Notifications (with Streaming only)noyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingSharding via remote tablesShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)Internal replication in Colossus, and regional replication between two clusters in different zonesnone infoSource-replica replication available in experimental statusMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACIDACID
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)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standard

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More resources
BangdbGoogle Cloud BigtableMonetDBSplice Machine
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