DBMS > Dragonfly vs. GridGain vs. OpenTenBase

System Properties Comparison Dragonfly vs. GridGain vs. OpenTenBase

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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

GridGain is an in-memory computing platform, built on Apache Ignite

An enterprise-level distributed HTAP open source database based on PostgreSQL

Primary database model

Key-value store

Columnar
Key-value store
Object oriented DBMS
Relational DBMS

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	1.48
Rank	#150	Overall
	#1	Columnar
	#26	Key-value stores
	#2	Object oriented DBMS
	#69	Relational DBMS

Score	0.00
Rank	#385	Overall
	#159	Relational DBMS

Website

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

www.gridgain.com

github.com/OpenTenBase/OpenTenBase
www.opentenbase.org

Technical documentation

www.dragonflydb.io/docs

www.gridgain.com/docs/index.html

docs.opentenbase.org
docs.opentenbase.org/en

Developer

DragonflyDB team and community contributors

GridGain Systems, Inc.

OpenAtom Foundation, previously Tencent

Initial release

2023

2007

Current release

1.0, March 2023

GridGain 8.5.1

2.5, January 2024

License

Commercial or Open Source

Open Source

BSL 1.1

commercial, open source

Open Source

BSD-3

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++, .Net, Python, REST, SQL

Server operating systems

Linux

Linux
OS X
Solaris
Windows
z/OS

Linux

Data scheme

scheme-free

yes

Typing

predefined data types such as float or date

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

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

Secondary indexes

yes

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

yes

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

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

C#
C++
Java
PHP
Python
Ruby
Scala

C
Go
Java
PHP
Python

Server-side scripts

Stored procedures

Lua

yes (compute grid and cache interceptors can be used instead)

Triggers

publish/subscribe channels provide some trigger functionality

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes (replicated cache)

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

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

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

Role-based access control
Security Hooks for custom implementations

Access rights for users, groups and roles according to SQL-standard

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