DBMS > Dragonfly vs. EJDB vs. Galaxybase vs. IBM Db2 Event Store

System Properties Comparison Dragonfly vs. EJDB vs. Galaxybase vs. IBM Db2 Event Store

Please select another system to include it in the comparison.

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)

Scalable, ACID-compliant native distributed parallel graph platform

Distributed Event Store optimized for Internet of Things use cases

Primary database model

Key-value store

Document store

Graph DBMS

Event Store
Time Series DBMS

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

Score	0.49
Rank	#261	Overall
	#38	Key-value stores

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	0.07
Rank	#377	Overall
	#40	Graph DBMS

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Website

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

github.com/Softmotions/ejdb

galaxybase.com

www.ibm.com/products/db2-event-store

Technical documentation

www.dragonflydb.io/docs

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

www.ibm.com/docs/en/db2-event-store

Developer

DragonflyDB team and community contributors

Softmotions

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

IBM

Initial release

2023

2012

2017

Current release

1.0, March 2023

Nov 20, November 2021

2.0

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

GPLv2

commercial

free developer edition available

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++

C and Java

C and C++

Server operating systems

Linux

server-less

Linux

Linux, macOS, Windows for the developer addition

Data scheme

scheme-free

schema-free

Strong typed schema

yes

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

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.

Secondary indexes

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

in-process shared library

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

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

Go
Java
Python

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

Server-side scripts

Stored procedures

Lua

user defined procedures and functions

yes

Triggers

publish/subscribe channels provide some trigger functionality

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

Active-active shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Relationships in graphs

Transaction concepts

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

Atomic execution of command blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

yes

Read/Write Locking

yes

No - written data is immutable

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

Role-based access control

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

DragonflyDB Announces $21m in New Funding and General Availability
21 March 2023, businesswire.com

DragonflyDB reels in $21M for its speedy in-memory database
21 March 2023, SiliconANGLE News

Dragonfly 1.0 Released For What Claims To Be The World's Fastest In-Memory Data Store
20 March 2023, Phoronix

Intel Linux Kernel Optimizations Show Huge Benefit For High Core Count Servers
29 March 2023, Phoronix

SFU Computing Science researchers receive 2022 ACM SIGMOD Research Highlight Award.
24 February 2023, Simon Fraser University News

provided by Google News

Advancements in streaming data storage, real-time analysis and machine learning
25 July 2019, ibm.com

How IBM Is Turning Db2 into an ‘AI Database’
3 June 2019, Datanami

Best cloud databases of 2022
4 October 2022, ITPro

Why a robust data management strategy is essential today | IBM HDM
19 September 2019, Express Computer

provided by Google News

Share this page