DBMS > Apache Druid vs. ArcadeDB vs. Badger vs. Postgres-XL

System Properties Comparison Apache Druid vs. ArcadeDB vs. Badger vs. Postgres-XL

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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

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

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

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Relational DBMS
Time Series DBMS

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Key-value store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	2.85
Rank	#96	Overall
	#50	Relational DBMS
	#6	Time Series DBMS

Score	0.02
Rank	#374	Overall
	#52	Document stores
	#38	Graph DBMS
	#56	Key-value stores
	#38	Time Series DBMS

Score	0.14
Rank	#328	Overall
	#48	Key-value stores

Score	0.43
Rank	#260	Overall
	#119	Relational DBMS

Website

druid.apache.org

arcadedb.com

github.com/dgraph-io/badger

www.postgres-xl.org

Technical documentation

druid.apache.org/docs/latest/design

docs.arcadedb.com

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

www.postgres-xl.org/documentation

Developer

Apache Software Foundation and contributors

Arcade Data

DGraph Labs

Initial release

2012

2021

2017

2014

since 2012, originally named StormDB

Current release

30.0.0, June 2024

September 2021

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

Mozilla public license

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

All OS with a Java VM

BSD
Linux
OS X
Solaris
Windows

Linux
macOS

Data scheme

yes

schema-less columns are supported

schema-free

yes

Typing

predefined data types such as float or date

yes

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

SQL-like query language, no joins

yes

distributed, parallel query execution

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Java

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Transaction concepts

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

ACID

MVCC

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.

User concepts

Access control

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

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

Imply Announces the Availability of Imply Polaris, a Database-as-a-Service Built from Apache Druid, on Microsoft Azure
26 June 2024, businesswire.com

'Lucifer' Botnet Turns Up the Heat on Apache Hadoop Servers
21 February 2024, Dark Reading

New DDoS malware Attacking Apache big-data stack, Hadoop, & Druid Servers
26 February 2024, GBHackers

Apache® Druid Wins Best Big Data Product in the 2023 BigDATAwire Readers’ Choice Awards
26 January 2024, businesswire.com

Apache Druid Takes Its Place In The Pantheon Of Databases
16 June 2022, The Next Platform

provided by Google News

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31 July 2019, VentureBeat

provided by Google News

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