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DBMS > Drizzle vs. Google Cloud Bigtable vs. Microsoft Azure AI Search vs. Oracle Rdb vs. Sequoiadb

System Properties Comparison Drizzle vs. Google Cloud Bigtable vs. Microsoft Azure AI Search vs. Oracle Rdb vs. Sequoiadb

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Azure AI Search  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.
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.Search-as-a-service for web and mobile app developmentNewSQL database with distributed OLTP and SQL
Primary database modelRelational DBMSKey-value store
Wide column store
Search engineRelational DBMSDocument store
Relational DBMS
Secondary database modelsVector 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
Score5.72
Rank#66  Overall
#8  Search engines
Score1.23
Rank#180  Overall
#82  Relational DBMS
Score0.50
Rank#264  Overall
#42  Document stores
#121  Relational DBMS
Websitecloud.google.com/­bigtableazure.microsoft.com/­en-us/­services/­searchwww.oracle.com/­database/­technologies/­related/­rdb.htmlwww.sequoiadb.com
Technical documentationcloud.google.com/­bigtable/­docslearn.microsoft.com/­en-us/­azure/­searchwww.oracle.com/­database/­technologies/­related/­rdb-doc.htmlwww.sequoiadb.com/­en/­index.php?m=Files&a=index
DeveloperDrizzle project, originally started by Brian AkerGoogleMicrosoftOracle, originally developed by Digital Equipment Corporation (DEC)Sequoiadb Ltd.
Initial release20082015201519842013
Current release7.2.4, September 2012V17.4.1.1, 2021
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialcommercialcommercialOpen Source infoServer: AGPL; Client: Apache V2
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++
Server operating systemsFreeBSD
Linux
OS X
hostedhostedHP Open VMSLinux
Data schemeyesschema-freeyesFlexible Schema (defined schema, partial schema, schema free)schema-free
Typing infopredefined data types such as float or dateyesnoyesyesyes 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 indexesyesnoyesyesyes
SQL infoSupport of SQLyes infowith proprietary extensionsnonoyesSQL-like query language
APIs and other access methodsJDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
RESTful HTTP APIproprietary protocol using JSON
Supported programming languagesC
C++
Java
PHP
C#
C++
Go
Java
JavaScript (Node.js)
Python
C#
Java
JavaScript
Python
.Net
C++
Java
PHP
Python
Server-side scripts infoStored proceduresnononoJavaScript
Triggersno infohooks for callbacks inside the server can be used.nonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceSharding
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 zonesyes infoImplicit feature of the cloud serviceSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsnoyes, 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.nononono
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)yes infousing Azure authenticationsimple password-based access control

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More resources
DrizzleGoogle Cloud BigtableMicrosoft Azure AI SearchOracle RdbSequoiadb
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