DBMS > Apache Druid vs. Drizzle vs. Prometheus vs. SQLite

System Properties Comparison Apache Druid vs. Drizzle vs. Prometheus vs. SQLite

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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

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Open-source Time Series DBMS and monitoring system

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

druid.apache.org

prometheus.io

www.sqlite.org

Technical documentation

druid.apache.org/docs/latest/design

prometheus.io/docs

www.sqlite.org/docs.html

Developer

Apache Software Foundation and contributors

Drizzle project, originally started by Brian Aker

Dwayne Richard Hipp

Initial release

2012

2008

2015

2000

Current release

29.0.1, April 2024

7.2.4, September 2012

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

GNU GPL

Open Source

Apache 2.0

Open Source

Public Domain

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

Java

C++

Server operating systems

Linux
OS X
Unix

FreeBSD
Linux
OS X

Linux
Windows

server-less

Data scheme

yes

schema-less columns are supported

yes

dynamic column types

Typing

predefined data types such as float or date

yes

Numeric data only

yes

not rigid because of 'dynamic typing' concept.

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.

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

yes

with proprietary extensions

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC

RESTful HTTP/JSON API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C
C++
Java
PHP

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Multi-source replication
Source-replica replication

yes

by Federation

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Pluggable authentication mechanisms

e.g. LDAP, HTTP

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