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DBMS > Drizzle vs. Google Cloud Bigtable vs. HBase vs. OrigoDB

System Properties Comparison Drizzle vs. Google Cloud Bigtable vs. HBase vs. OrigoDB

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHBase  Xexclude from comparisonOrigoDB  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.Wide-column store based on Apache Hadoop and on concepts of BigTableA fully ACID in-memory object graph database
Primary database modelRelational DBMSKey-value store
Wide column store
Wide column storeDocument store
Object oriented 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
Score30.50
Rank#26  Overall
#2  Wide column stores
Score0.00
Rank#383  Overall
#53  Document stores
#20  Object oriented DBMS
Websitecloud.google.com/­bigtablehbase.apache.orgorigodb.com
Technical documentationcloud.google.com/­bigtable/­docshbase.apache.org/­book.htmlorigodb.com/­docs
DeveloperDrizzle project, originally started by Brian AkerGoogleApache Software Foundation infoApache top-level project, originally developed by PowersetRobert Friberg et al
Initial release2008201520082009 infounder the name LiveDB
Current release7.2.4, September 20122.3.4, January 2021
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialOpen Source infoApache version 2Open Source
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC#
Server operating systemsFreeBSD
Linux
OS X
hostedLinux
Unix
Windows infousing Cygwin
Linux
Windows
Data schemeyesschema-freeschema-free, schema definition possibleyes
Typing infopredefined data types such as float or dateyesnooptions to bring your own types, AVROUser defined using .NET types and collections
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.nonono infocan be achieved using .NET
Secondary indexesyesnonoyes
SQL infoSupport of SQLyes infowith proprietary extensionsnonono
APIs and other access methodsJDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Java API
RESTful HTTP API
Thrift
.NET Client API
HTTP API
LINQ
Supported programming languagesC
C++
Java
PHP
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
Server-side scripts infoStored proceduresnonoyes infoCoprocessors in Javayes
Triggersno infohooks for callbacks inside the server can be used.noyesyes infoDomain Events
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardinghorizontal partitioning infoclient side managed; servers are not synchronized
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
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesno
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
Foreign keys infoReferential integrityyesnonodepending on model
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsSingle row ACID (across millions of columns)ACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoWrite ahead log
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
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 Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACRole based authorization

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More resources
DrizzleGoogle Cloud BigtableHBaseOrigoDB
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