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DBMS > Drizzle vs. Google Cloud Datastore vs. HBase vs. Trafodion

System Properties Comparison Drizzle vs. Google Cloud Datastore vs. HBase vs. Trafodion

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHBase  Xexclude from comparisonTrafodion  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.Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformWide-column store based on Apache Hadoop and on concepts of BigTableTransactional SQL-on-Hadoop DBMS
Primary database modelRelational DBMSDocument storeWide column storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score27.97
Rank#26  Overall
#2  Wide column stores
Websitecloud.google.com/­datastorehbase.apache.orgtrafodion.apache.org
Technical documentationcloud.google.com/­datastore/­docshbase.apache.org/­book.htmltrafodion.apache.org/­documentation.html
DeveloperDrizzle project, originally started by Brian AkerGoogleApache Software Foundation infoApache top-level project, originally developed by PowersetApache Software Foundation, originally developed by HP
Initial release2008200820082014
Current release7.2.4, September 20122.3.4, January 20212.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialOpen Source infoApache version 2Open Source infoApache 2.0
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++, Java
Server operating systemsFreeBSD
Linux
OS X
hostedLinux
Unix
Windows infousing Cygwin
Linux
Data schemeyesschema-freeschema-free, schema definition possibleyes
Typing infopredefined data types such as float or dateyesyes, details hereoptions to bring your own types, AVROyes
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
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyes infowith proprietary extensionsSQL-like query language (GQL)noyes
APIs and other access methodsJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RESTful HTTP API
Thrift
ADO.NET
JDBC
ODBC
Supported programming languagesC
C++
Java
PHP
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresnousing Google App Engineyes infoCoprocessors in JavaJava Stored Procedures
Triggersno infohooks for callbacks inside the server can be used.Callbacks using the Google Apps Engineyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication using PaxosMulti-source replication
Source-replica replication
yes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyesyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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.Immediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsSingle row ACID (across millions of columns)ACID
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.noyesno
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 & ABACfine grained access rights according to SQL-standard

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More resources
DrizzleGoogle Cloud DatastoreHBaseTrafodion
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