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DBMS > Drizzle vs. etcd vs. Fauna vs. Google Cloud Bigtable vs. Microsoft Azure SQL Database

System Properties Comparison Drizzle vs. etcd vs. Fauna vs. Google Cloud Bigtable vs. Microsoft Azure SQL Database

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonetcd  Xexclude from comparisonFauna infopreviously named FaunaDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  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.A distributed reliable key-value storeFauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Database as a Service offering with high compatibility to Microsoft SQL Server
Primary database modelRelational DBMSKey-value storeDocument store
Graph DBMS
Relational DBMS
Time Series DBMS
Key-value store
Wide column store
Relational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.64
Rank#54  Overall
#5  Key-value stores
Score1.55
Rank#154  Overall
#26  Document stores
#14  Graph DBMS
#72  Relational DBMS
#13  Time Series DBMS
Score3.58
Rank#92  Overall
#14  Key-value stores
#8  Wide column stores
Score78.40
Rank#15  Overall
#10  Relational DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
fauna.comcloud.google.com/­bigtableazure.microsoft.com/­en-us/­products/­azure-sql/­database
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.fauna.comcloud.google.com/­bigtable/­docsdocs.microsoft.com/­en-us/­azure/­azure-sql
DeveloperDrizzle project, originally started by Brian AkerFauna, Inc.GoogleMicrosoft
Initial release2008201420152010
Current release7.2.4, September 20123.4, August 2019V12
License infoCommercial or Open SourceOpen Source infoGNU GPLOpen Source infoApache Version 2.0commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++GoScalaC++
Server operating systemsFreeBSD
Linux
OS X
FreeBSD
Linux
Windows infoexperimental
hostedhostedhosted
Data schemeyesschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnononoyes
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.nononoyes
Secondary indexesyesnoyesnoyes
SQL infoSupport of SQLyes infowith proprietary extensionsnononoyes
APIs and other access methodsJDBCgRPC
JSON over HTTP
RESTful HTTP APIgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
JDBC
ODBC
Supported programming languagesC
C++
Java
PHP
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnonouser defined functionsnoTransact SQL
Triggersno infohooks for callbacks inside the server can be used.yes, watching key changesnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoconsistent hashingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replicationInternal replication in Colossus, and regional replication between two clusters in different zonesyes, with always 3 replicas available
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integrityyesnoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDAtomic single-row operationsACID
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, HTTPnoIdentity management, authentication, and access controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
DrizzleetcdFauna infopreviously named FaunaDBGoogle Cloud BigtableMicrosoft Azure SQL Database infoformerly SQL Azure
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