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

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

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMonetDB  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.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Google'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 modelRelational DBMSKey-value store
Wide column store
Relational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
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
Websitecloud.google.com/­bigtablewww.monetdb.orgsplicemachine.com
Technical documentationcloud.google.com/­bigtable/­docswww.monetdb.org/­Documentationsplicemachine.com/­how-it-works
DeveloperDrizzle project, originally started by Brian AkerGoogleMonetDB BVSplice Machine
Initial release2008201520042014
Current release7.2.4, September 2012Dec2023 (11.49), December 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialOpen 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++CJava
Server operating systemsFreeBSD
Linux
OS X
hostedFreeBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyes
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.no
Secondary indexesyesnoyesyes
SQL infoSupport of SQLyes infowith proprietary extensionsnoyes infoSQL 2003 with some extensionsyes
APIs and other access methodsJDBCgRPC (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++
Java
PHP
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
Triggersno infohooks for callbacks inside the server can be used.noyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding via remote tablesShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
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 systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integrityyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess 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
DrizzleGoogle Cloud BigtableMonetDBSplice Machine
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