DBMS > Apache Druid vs. Badger vs. Prometheus vs. SiriDB vs. SQLite

System Properties Comparison Apache Druid vs. Badger vs. Prometheus vs. SiriDB vs. SQLite

Editorial information provided by DB-Engines

Name

Description

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

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

Open-source Time Series DBMS and monitoring system

Open Source Time Series DBMS

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS
Time Series DBMS

Key-value store

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	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Score	0.07
Rank	#378	Overall
	#42	Time Series DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

druid.apache.org

github.com/dgraph-io/badger

prometheus.io

siridb.com

www.sqlite.org

Technical documentation

druid.apache.org/docs/latest/design

godoc.org/github.com/dgraph-io/badger

prometheus.io/docs

docs.siridb.com

www.sqlite.org/docs.html

Developer

Apache Software Foundation and contributors

DGraph Labs

Cesbit

Dwayne Richard Hipp

Initial release

2012

2017

2015

2017

2000

Current release

29.0.1, April 2024

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

MIT License

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

Linux
OS X
Unix

BSD
Linux
OS X
Solaris
Windows

Linux
Windows

Linux

server-less

Data scheme

yes

schema-less columns are supported

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

Numeric data only

yes

Numeric data

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

SQL-92 is not fully supported

APIs and other access methods

JDBC
RESTful HTTP/JSON API

RESTful HTTP/JSON API

HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

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

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

none

yes

by Federation

yes

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

simple rights management via user accounts

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