DBMS > Dragonfly vs. Ehcache vs. GridDB

System Properties Comparison Dragonfly vs. Ehcache vs. GridDB

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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

A widely adopted Java cache with tiered storage options

Scalable in-memory time series database optimized for IoT and Big Data

Primary database model

Key-value store

Time Series DBMS

Secondary database models

Key-value store
Relational DBMS

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

Score	0.44
Rank	#255	Overall
	#38	Key-value stores

Score	4.79
Rank	#66	Overall
	#8	Key-value stores

Score	1.91
Rank	#123	Overall
	#10	Time Series DBMS

Website

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

www.ehcache.org

griddb.net

Technical documentation

www.dragonflydb.io/docs

www.ehcache.org/documentation

docs.griddb.net

Developer

DragonflyDB team and community contributors

Terracotta Inc, owned by Software AG

Toshiba Corporation

Initial release

2023

2009

2013

Current release

1.0, March 2023

3.10.0, March 2022

5.1, August 2022

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

Apache Version 2; commercial licenses available

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also 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++

Java

C++

Server operating systems

Linux

All OS with a Java VM

Linux

Data scheme

scheme-free

schema-free

yes

Typing

predefined data types such as float or date

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

yes

numerical, string, blob, geometry, boolean, timestamp

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

SQL92, SQL-like TQL (Toshiba Query Language)

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

JCache

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON 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

Java

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

Lua

Triggers

publish/subscribe channels provide some trigger functionality

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

by using Terracotta Server

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Tunable Consistency (Strong, Eventual, Weak)

Immediate consistency within container, eventual consistency across containers

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of command blocks and scripts

yes

supports JTA and can work as an XA resource

ACID at container level

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

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 rights for users can be defined per database

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