DBMS > Dragonfly vs. Graph Engine vs. ITTIA

System Properties Comparison Dragonfly vs. Graph Engine vs. ITTIA

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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

Edge Time Series DBMS with Real-Time Stream Processing

Primary database model

Key-value store

Graph DBMS
Key-value store

Time Series DBMS

Secondary database models

Relational DBMS

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

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

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	0.44
Rank	#267	Overall
	#23	Time Series DBMS

Website

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

www.graphengine.io

www.ittia.com

Technical documentation

www.dragonflydb.io/docs

www.graphengine.io/docs/manual

Developer

DragonflyDB team and community contributors

Microsoft

ITTIA L.L.C.

Initial release

2023

2010

2007

Current release

1.0, March 2023

8.7

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

MIT License

commercial

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++

.NET and C

C and C++

Server operating systems

Linux

.NET

Linux
Windows

Data scheme

scheme-free

yes

Fixed schema

Typing

predefined data types such as float or date

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

yes

Float/Blob/Integer/String/Unicode/Date/Time/Timestamp/Interval

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

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

RESTful HTTP API

JDBC
ODBC
RESTful HTTP API
WebSocket

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

C
C++
JavaScript (Node.js)
Python

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

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual 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

yes

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

yes

yes, multi-version concurrency control (MVCC)

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

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

Database file passwords

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More resources

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