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

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

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonOracle Rdb  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.FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.A .NET NoSQL DBMS that can integrate with and extend SQL Server.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.NewSQL database with distributed OLTP and SQL
Primary database modelRelational DBMSDocument store
Key-value store
Key-value store
Wide column store
Relational DBMSDocument store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.86
Rank#90  Overall
#13  Key-value stores
#7  Wide column stores
Score1.23
Rank#180  Overall
#82  Relational DBMS
Score0.50
Rank#264  Overall
#42  Document stores
#121  Relational DBMS
Websitecloud.google.com/­bigtablewww.oracle.com/­database/­technologies/­related/­rdb.htmlwww.sequoiadb.com
Technical documentationcloud.google.com/­bigtable/­docswww.oracle.com/­database/­technologies/­related/­rdb-doc.htmlwww.sequoiadb.com/­en/­index.php?m=Files&a=index
DeveloperDrizzle project, originally started by Brian AkerFatCloudGoogleOracle, originally developed by Digital Equipment Corporation (DEC)Sequoiadb Ltd.
Initial release20082012201519842013
Current release7.2.4, September 20127.4.1.1, 2021
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialcommercialcommercialOpen Source infoServer: AGPL; Client: Apache V2
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C#C++
Server operating systemsFreeBSD
Linux
OS X
WindowshostedHP Open VMSLinux
Data schemeyesschema-freeschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-free
Typing infopredefined data types such as float or dateyesyesnoyesyes 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.nonono
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLyes infowith proprietary extensionsno infoVia inetgration in SQL ServernoyesSQL-like query language
APIs and other access methodsJDBC.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
proprietary protocol using JSON
Supported programming languagesC
C++
Java
PHP
C#C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C++
Java
PHP
Python
Server-side scripts infoStored proceduresnoyes infovia applicationsnoJavaScript
Triggersno infohooks for callbacks inside the server can be used.yes infovia applicationsnono
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
selectable replication factorInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoAtomic single-row operationsyes, on a single nodeDocument is locked during a transaction
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPno infoCan implement custom security layer via applicationsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)simple password-based access control

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More resources
DrizzleFatDBGoogle Cloud BigtableOracle RdbSequoiadb
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