DBMS > Apache Druid vs. Badger vs. Dragonfly vs. EJDB vs. RocksDB

System Properties Comparison Apache Druid vs. Badger vs. Dragonfly vs. EJDB vs. RocksDB

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.

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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

Primary database model

Relational DBMS
Time Series DBMS

Key-value store

Document store

Key-value store

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	0.49
Rank	#261	Overall
	#38	Key-value stores

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

druid.apache.org

github.com/dgraph-io/badger

github.com/dragonflydb/dragonfly
www.dragonflydb.io

github.com/Softmotions/ejdb

rocksdb.org

Technical documentation

druid.apache.org/docs/latest/design

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

www.dragonflydb.io/docs

github.com/Softmotions/ejdb/blob/master/README.md

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation and contributors

DGraph Labs

DragonflyDB team and community contributors

Softmotions

Facebook, Inc.

Initial release

2012

2017

2023

2012

2013

Current release

29.0.1, April 2024

1.0, March 2023

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache 2.0

Open Source

BSL 1.1

Open Source

GPLv2

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

BSD
Linux
OS X
Solaris
Windows

Linux

server-less

Linux

Data scheme

yes

schema-less columns are supported

schema-free

scheme-free

schema-free

Typing

predefined data types such as float or date

yes

strings, hashes, lists, sets, sorted sets, bit arrays

yes

string, integer, double, bool, date, object_id

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

SQL

Support of SQL

SQL for querying

APIs and other access methods

JDBC
RESTful HTTP/JSON API

Proprietary protocol

RESP - REdis Serialization Protocol

in-process shared library

C++ API
Java API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Lua

Triggers

publish/subscribe channels provide some trigger functionality

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

none

Source-replica replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

Atomic execution of command blocks and scripts

yes

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

yes

Read/Write Locking

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

Password-based authentication

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