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DBMS > Dragonfly vs. Drizzle vs. Hawkular Metrics vs. KeyDB

System Properties Comparison Dragonfly vs. Drizzle vs. Hawkular Metrics vs. KeyDB

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Editorial information provided by DB-Engines
NameDragonfly  Xexclude from comparisonDrizzle  Xexclude from comparisonHawkular Metrics  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.
DescriptionA drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols
Primary database modelKey-value storeRelational DBMSTime Series DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.44
Rank#255  Overall
#38  Key-value stores
Score0.01
Rank#377  Overall
#39  Time Series DBMS
Score0.63
Rank#232  Overall
#32  Key-value stores
Websitegithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
www.hawkular.orggithub.com/­Snapchat/­KeyDB
keydb.dev
Technical documentationwww.dragonflydb.io/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.keydb.dev
DeveloperDragonflyDB team and community contributorsDrizzle project, originally started by Brian AkerCommunity supported by Red HatEQ Alpha Technology Ltd.
Initial release2023200820142019
Current release1.0, March 20237.2.4, September 2012
License infoCommercial or Open SourceOpen Source infoBSL 1.1Open Source infoGNU GPLOpen Source infoApache 2.0Open Source infoBSD-3
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++JavaC++
Server operating systemsLinuxFreeBSD
Linux
OS X
Linux
OS X
Windows
Linux
Data schemescheme-freeyesschema-freeschema-free
Typing infopredefined data types such as float or datestrings, hashes, lists, sets, sorted sets, bit arraysyesyespartial 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 indexesnoyesnoyes infoby using the Redis Search module
SQL infoSupport of SQLnoyes infowith proprietary extensionsnono
APIs and other access methodsProprietary protocol infoRESP - REdis Serialization ProtocolJDBCHTTP RESTProprietary protocol infoRESP - REdis Serialization Protoco
Supported programming languagesC
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl
C
C++
Java
PHP
Go
Java
Python
Ruby
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 proceduresLuanonoLua
Triggerspublish/subscribe channels provide some trigger functionalityno infohooks for callbacks inside the server can be used.yes infovia Hawkular Alertingno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
selectable replication factor infobased on CassandraMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Strong eventual consistency with CRDTs
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of command blocks and scriptsACIDnoOptimistic locking, atomic execution of commands blocks and scripts
Concurrency infoSupport for concurrent manipulation of datayes, strict serializability by the serveryesyesyes
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.yesnoyes
User concepts infoAccess controlPassword-based authenticationPluggable authentication mechanisms infoe.g. LDAP, HTTPnosimple password-based access control and ACL

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More resources
DragonflyDrizzleHawkular MetricsKeyDB
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