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DBMS > Drizzle vs. Google Cloud Bigtable vs. Google Cloud Datastore vs. IBM Db2

System Properties Comparison Drizzle vs. Google Cloud Bigtable vs. Google Cloud Datastore vs. IBM Db2

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIBM Db2 infoformerly named DB2 or IBM Database 2  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.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformCommon in IBM host environments, 2 different versions for host and Windows/Linux
Primary database modelRelational DBMSKey-value store
Wide column store
Document storeRelational DBMS infoSince Version 10.5 support for JSON/BSON documents compatible with MongoDB
Secondary database modelsDocument store
RDF store infoin Db2 LUW (Linux, Unix, Windows)
Spatial DBMS infowith Db2 Spatial Extender
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
Score4.47
Rank#76  Overall
#12  Document stores
Score128.46
Rank#8  Overall
#5  Relational DBMS
Websitecloud.google.com/­bigtablecloud.google.com/­datastorewww.ibm.com/­products/­db2
Technical documentationcloud.google.com/­bigtable/­docscloud.google.com/­datastore/­docswww.ibm.com/­docs/­en/­db2
DeveloperDrizzle project, originally started by Brian AkerGoogleGoogleIBM
Initial release2008201520081983 infohost version
Current release7.2.4, September 201212.1, October 2016
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialcommercialcommercial infofree version is available
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C and C++
Server operating systemsFreeBSD
Linux
OS X
hostedhostedAIX
HP-UX
Linux
Solaris
Windows
z/OS
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnoyes, details hereyes
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 indexesyesnoyesyes
SQL infoSupport of SQLyes infowith proprietary extensionsnoSQL-like query language (GQL)yes
APIs and other access methodsJDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
JSON style queries infoMongoDB compatible
ODBC
XQuery
Supported programming languagesC
C++
Java
PHP
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic
Server-side scripts infoStored proceduresnonousing Google App Engineyes
Triggersno infohooks for callbacks inside the server can be used.noCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infoonly with Windows/Unix/Linux Version
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 zonesMulti-source replication using Paxosyes infowith separate tools (MQ, InfoSphere)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infousing Google Cloud Dataflowno
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 or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.
Foreign keys infoReferential integrityyesnoyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nono
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)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
DrizzleGoogle Cloud BigtableGoogle Cloud DatastoreIBM Db2 infoformerly named DB2 or IBM Database 2
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