DBMS > Apache Druid vs. Prometheus vs. RocksDB

System Properties Comparison Apache Druid vs. Prometheus vs. RocksDB

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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

Open-source Time Series DBMS and monitoring system

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Relational DBMS
Time Series DBMS

Time Series DBMS

Key-value store

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

Score	3.29
Rank	#95	Overall
	#49	Relational DBMS
	#7	Time Series DBMS

Score	7.92
Rank	#51	Overall
	#2	Time Series DBMS

Score	4.00
Rank	#84	Overall
	#11	Key-value stores

Website

druid.apache.org

prometheus.io

rocksdb.org

Technical documentation

druid.apache.org/docs/latest/design

prometheus.io/docs

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation and contributors

Facebook, Inc.

Initial release

2012

2015

2013

Current release

29.0.1, April 2024

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache 2.0

Open Source

BSD

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

Java

C++

Server operating systems

Linux
OS X
Unix

Linux
Windows

Linux

Data scheme

yes

schema-less columns are supported

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data only

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

APIs and other access methods

JDBC
RESTful HTTP/JSON API

RESTful HTTP/JSON API

C++ API
Java API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

by Federation

yes

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

Transaction concepts

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

yes

Concurrency

Support for concurrent manipulation of data

yes

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

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