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

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

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonKeyDB  Xexclude from comparisonTimesTen  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.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 protocolsAn in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.
Primary database modelRelational DBMSTime Series DBMSKey-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.01
Rank#377  Overall
#39  Time Series DBMS
Score0.63
Rank#232  Overall
#32  Key-value stores
Score1.26
Rank#164  Overall
#75  Relational DBMS
Websitewww.hawkular.orggithub.com/­Snapchat/­KeyDB
keydb.dev
www.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.keydb.devdocs.oracle.com/­en/­database/­other-databases/­timesten/­index.html
DeveloperDrizzle project, originally started by Brian AkerCommunity supported by Red HatEQ Alpha Technology Ltd.Oracle infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release2008201420191998
Current release7.2.4, September 2012Release 22.1
License infoCommercial or Open SourceOpen Source infoGNU GPLOpen Source infoApache 2.0Open Source infoBSD-3commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC++
Server operating systemsFreeBSD
Linux
OS X
Linux
OS X
Windows
LinuxIBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyespartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesyes
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 indexesyesnoyes infoby using the Redis Search moduleyes
SQL infoSupport of SQLyes infowith proprietary extensionsnonoyes
APIs and other access methodsJDBCHTTP RESTProprietary protocol infoRESP - REdis Serialization ProtocoODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC
Supported programming languagesC
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
C
C++
Java
Node.js
PL/SQL
Python
Server-side scripts infoStored proceduresnonoLuaPL/SQL
Triggersno infohooks for callbacks inside the server can be used.yes infovia Hawkular Alertingnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
selectable replication factor infobased on CassandraMulti-source replication
Source-replica replication
Multi-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 Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Strong eventual consistency with CRDTs
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoOptimistic locking, atomic execution of commands blocks and scriptsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPnosimple password-based access control and ACLfine grained access rights according to SQL-standard

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More resources
DrizzleHawkular MetricsKeyDBTimesTen
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