DBMS > Dragonfly vs. EJDB vs. HBase

System Properties Comparison Dragonfly vs. EJDB vs. HBase

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Editorial information provided by DB-Engines

Name

Description

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)

Wide-column store based on Apache Hadoop and on concepts of BigTable

Primary database model

Key-value store

Document store

Wide column store

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

Score	0.41
Rank	#266	Overall
	#38	Key-value stores

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Website

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

github.com/Softmotions/ejdb

hbase.apache.org

Technical documentation

www.dragonflydb.io/docs

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

hbase.apache.org/book.html

Developer

DragonflyDB team and community contributors

Softmotions

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Initial release

2023

2012

2008

Current release

1.0, March 2023

2.3.4, January 2021

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

GPLv2

Open Source

Apache version 2

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

C++

Java

Server operating systems

Linux

server-less

Linux
Unix
Windows

using Cygwin

Data scheme

scheme-free

schema-free

schema-free, schema definition possible

Typing

predefined data types such as float or date

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

yes

string, integer, double, bool, date, object_id

options to bring your own types, AVRO

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

SQL

Support of SQL

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

in-process shared library

Java API
RESTful HTTP API
Thrift

Supported programming languages

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#
C++
Groovy
Java
PHP
Python
Scala

Server-side scripts

Stored procedures

Lua

yes

Coprocessors in Java

Triggers

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency or 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

Single row ACID (across millions of columns)

Concurrency

Support for concurrent manipulation of data

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

Password-based authentication

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

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More resources

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13 May 2013, Paul Andlinger

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