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

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

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

MySQL 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 model

Relational DBMS

Time Series DBMS

Key-value store

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.28
Rank	#287	Overall
	#131	Relational DBMS

Score	0.01
Rank	#377	Overall
	#39	Time Series DBMS

Score	0.63
Rank	#232	Overall
	#32	Key-value stores

Website

github.com/datafuselabs/databend
www.databend.com

www.hawkular.org

github.com/Snapchat/KeyDB
keydb.dev

Technical documentation

docs.databend.com

www.hawkular.org/hawkular-metrics/docs/user-guide

docs.keydb.dev

Developer

Databend Labs

Drizzle project, originally started by Brian Aker

Community supported by Red Hat

EQ Alpha Technology Ltd.

Initial release

2021

2008

2014

2019

Current release

1.0.59, April 2023

7.2.4, September 2012

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

GNU GPL

Open Source

Apache 2.0

Open Source

BSD-3

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Rust

C++

Java

C++

Server operating systems

hosted
Linux
macOS

FreeBSD
Linux
OS X

Linux
OS X
Windows

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

by using the Redis Search module

SQL

Support of SQL

yes

with proprietary extensions

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

JDBC

HTTP REST

Proprietary protocol

RESP - REdis Serialization Protoco

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

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

Stored procedures

Lua

Triggers

hooks for callbacks inside the server can be used.

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency
Strong eventual consistency with CRDTs

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

yes

ACID

Optimistic locking, atomic execution of commands blocks and scripts

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Users with fine-grained authorization concept, user roles

Pluggable authentication mechanisms

e.g. LDAP, HTTP

simple password-based access control and ACL

More information provided by the system vendor

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

Has MySQL finally lost its mojo?
1 July 2013, Matthias Gelbmann

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