DBMS > Dragonfly vs. LevelDB vs. OrigoDB vs. Transwarp StellarDB vs. XTDB

System Properties Comparison Dragonfly vs. LevelDB vs. OrigoDB vs. Transwarp StellarDB vs. XTDB

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 fast key-value storage library that provides an ordered mapping from string keys to string values

A fully ACID in-memory object graph database

A distributed graph DBMS built for enterprise-level graph applications

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Key-value store

Document store
Object oriented DBMS

Graph DBMS

Document store

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

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

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	0.00
Rank	#383	Overall
	#39	Graph DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

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

github.com/google/leveldb

origodb.com

www.transwarp.cn/en/product/stellardb

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

www.dragonflydb.io/docs

github.com/google/leveldb/blob/main/doc/index.md

origodb.com/docs

www.xtdb.com/docs

Developer

DragonflyDB team and community contributors

Google

Robert Friberg et al

Transwarp

Juxt Ltd.

Initial release

2023

2011

2009

under the name LiveDB

2019

Current release

1.0, March 2023

1.23, February 2021

1.19, September 2021

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

BSD

Open Source

commercial

Open Source

MIT License

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++

Clojure

Server operating systems

Linux

Illumos
Linux
OS X
Windows

Linux
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

scheme-free

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

User defined using .NET types and collections

yes, extensible-data-notation format

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

limited SQL, making use of Apache Calcite

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

.NET Client API
HTTP API
LINQ

OpenCypher

HTTP REST
JDBC

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++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.Net

Clojure
Java

Server-side scripts

Stored procedures

Lua

yes

Triggers

publish/subscribe channels provide some trigger functionality

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

client side managed; servers are not synchronized

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Source-replica replication

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

depending on model

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

with automatic compression on writes

yes

Write ahead log

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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 authorization

yes

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