DBMS > Dragonfly vs. Graph Engine vs. TinkerGraph vs. Transwarp StellarDB

System Properties Comparison Dragonfly vs. Graph Engine vs. TinkerGraph vs. Transwarp StellarDB

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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 distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

A distributed graph DBMS built for enterprise-level graph applications

Primary database model

Key-value store

Graph DBMS
Key-value store

Graph DBMS

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

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

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	0.08
Rank	#348	Overall
	#35	Graph DBMS

Score	0.00
Rank	#383	Overall
	#39	Graph DBMS

Website

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

www.graphengine.io

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

www.transwarp.cn/en/product/stellardb

Technical documentation

www.dragonflydb.io/docs

www.graphengine.io/docs/manual

Developer

DragonflyDB team and community contributors

Microsoft

Transwarp

Initial release

2023

2010

2009

Current release

1.0, March 2023

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

MIT License

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

.NET and C

Java

Server operating systems

Linux

.NET

Data scheme

scheme-free

yes

schema-free

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.

Secondary indexes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

RESTful HTTP API

TinkerPop 3

OpenCypher

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++
F#
Visual Basic

Groovy
Java

Server-side scripts

Stored procedures

Lua

yes

Triggers

publish/subscribe channels provide some trigger functionality

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

none

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

Atomic execution of command blocks and scripts

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

optional

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

yes

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More resources

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