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DBMS > Drizzle vs. Google Cloud Bigtable vs. Oracle Rdb vs. PouchDB vs. Sequoiadb

System Properties Comparison Drizzle vs. Google Cloud Bigtable vs. Oracle Rdb vs. PouchDB vs. Sequoiadb

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonOracle Rdb  Xexclude from comparisonPouchDB  Xexclude from comparisonSequoiadb  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.JavaScript DBMS with an API inspired by CouchDBNewSQL database with distributed OLTP and SQL
Primary database modelRelational DBMSKey-value store
Wide column store
Relational DBMSDocument storeDocument store
Relational 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
Score1.08
Rank#184  Overall
#85  Relational DBMS
Score2.28
Rank#115  Overall
#21  Document stores
Score0.45
Rank#261  Overall
#41  Document stores
#122  Relational DBMS
Websitecloud.google.com/­bigtablewww.oracle.com/­database/­technologies/­related/­rdb.htmlpouchdb.comwww.sequoiadb.com
Technical documentationcloud.google.com/­bigtable/­docswww.oracle.com/­database/­technologies/­related/­rdb-doc.htmlpouchdb.com/­guideswww.sequoiadb.com/­en/­index.php?m=Files&a=index
DeveloperDrizzle project, originally started by Brian AkerGoogleOracle, originally developed by Digital Equipment Corporation (DEC)Apache Software FoundationSequoiadb Ltd.
Initial release20082015198420122013
Current release7.2.4, September 20127.4.1.1, 20217.1.1, June 2019
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialcommercialOpen SourceOpen Source infoServer: AGPL; Client: Apache V2
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaScriptC++
Server operating systemsFreeBSD
Linux
OS X
hostedHP Open VMSserver-less, requires a JavaScript environment (browser, Node.js)Linux
Data schemeyesschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free
Typing infopredefined data types such as float or dateyesnoyesnoyes infooid, date, timestamp, binary, regex
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.nononono
Secondary indexesyesnoyesyes infovia viewsyes
SQL infoSupport of SQLyes infowith proprietary extensionsnoyesnoSQL-like query language
APIs and other access methodsJDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP REST infoonly for PouchDB Server
JavaScript API
proprietary protocol using JSON
Supported programming languagesC
C++
Java
PHP
C#
C++
Go
Java
JavaScript (Node.js)
Python
JavaScript.Net
C++
Java
PHP
Python
Server-side scripts infoStored proceduresnonoView functions in JavaScriptJavaScript
Triggersno infohooks for callbacks inside the server can be used.noyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infowith a proxy-based framework, named couchdb-loungeSharding
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 infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsyes, on a single nodenoDocument is locked during a transaction
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
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)nosimple password-based access control

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More resources
DrizzleGoogle Cloud BigtableOracle RdbPouchDBSequoiadb
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