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DBMS > Drizzle vs. etcd vs. Heroic vs. Kinetica vs. Microsoft Azure SQL Database

System Properties Comparison Drizzle vs. etcd vs. Heroic vs. Kinetica vs. Microsoft Azure SQL Database

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonetcd  Xexclude from comparisonHeroic  Xexclude from comparisonKinetica  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 storeTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchFully vectorized database across both GPUs and CPUsDatabase as a Service offering with high compatibility to Microsoft SQL Server
Primary database modelRelational DBMSKey-value storeTime Series DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.05
Rank#53  Overall
#5  Key-value stores
Score0.13
Rank#335  Overall
#29  Time Series DBMS
Score0.42
Rank#261  Overall
#120  Relational DBMS
Score72.95
Rank#16  Overall
#11  Relational DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
github.com/­spotify/­heroicwww.kinetica.comazure.microsoft.com/­en-us/­products/­azure-sql/­database
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
spotify.github.io/­heroicdocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­azure-sql
DeveloperDrizzle project, originally started by Brian AkerSpotifyKineticaMicrosoft
Initial release2008201420122010
Current release7.2.4, September 20123.4, August 20197.1, August 2021V12
License infoCommercial or Open SourceOpen Source infoGNU GPLOpen Source infoApache Version 2.0Open Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++GoJavaC, C++C++
Server operating systemsFreeBSD
Linux
OS X
FreeBSD
Linux
Windows infoexperimental
Linuxhosted
Data schemeyesschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyesyes
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 indexesyesnoyes infovia Elasticsearchyesyes
SQL infoSupport of SQLyes infowith proprietary extensionsnonoSQL-like DML and DDL statementsyes
APIs and other access methodsJDBCgRPC
JSON over HTTP
HQL (Heroic Query Language, a JSON-based language)
HTTP API
JDBC
ODBC
RESTful HTTP API
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++
Java
JavaScript (Node.js)
Python
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnononouser defined functionsTransact SQL
Triggersno infohooks for callbacks inside the server can be used.yes, watching key changesnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
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.yesSource-replica replicationyes, with always 3 replicas available
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesnonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnononoACID
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.nonoyes infoGPU vRAM or System RAM
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPnoAccess rights for users and roles on table levelfine grained access rights according to SQL-standard

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More resources
DrizzleetcdHeroicKineticaMicrosoft Azure SQL Database infoformerly SQL Azure
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