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DBMS > Drizzle vs. etcd vs. Google Cloud Firestore vs. KeyDB

System Properties Comparison Drizzle vs. etcd vs. Google Cloud Firestore vs. KeyDB

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonetcd  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonKeyDB  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 storeCloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols
Primary database modelRelational DBMSKey-value storeDocument storeKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.25
Rank#54  Overall
#5  Key-value stores
Score7.85
Rank#51  Overall
#8  Document stores
Score0.71
Rank#226  Overall
#33  Key-value stores
Websiteetcd.io
github.com/­etcd-io/­etcd
firebase.google.com/­products/­firestoregithub.com/­Snapchat/­KeyDB
keydb.dev
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
firebase.google.com/­docs/­firestoredocs.keydb.dev
DeveloperDrizzle project, originally started by Brian AkerGoogleEQ Alpha Technology Ltd.
Initial release200820172019
Current release7.2.4, September 20123.4, August 2019
License infoCommercial or Open SourceOpen Source infoGNU GPLOpen Source infoApache Version 2.0commercialOpen Source infoBSD-3
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++GoC++
Server operating systemsFreeBSD
Linux
OS X
FreeBSD
Linux
Windows infoexperimental
hostedLinux
Data schemeyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesnoyespartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes
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 indexesyesnoyesyes infoby using the Redis Search module
SQL infoSupport of SQLyes infowith proprietary extensionsnonono
APIs and other access methodsJDBCgRPC
JSON over HTTP
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Proprietary protocol infoRESP - REdis Serialization Protoco
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
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
Server-side scripts infoStored proceduresnonoyes, Firebase Rules & Cloud FunctionsLua
Triggersno infohooks for callbacks inside the server can be used.yes, watching key changesyes, with Cloud Functionsno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
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 replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoUsing Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Strong eventual consistency with CRDTs
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoyesOptimistic locking, atomic execution of commands blocks and scripts
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logs
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.simple password-based access control and ACL

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More resources
DrizzleetcdGoogle Cloud FirestoreKeyDB
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