DBMS > Dgraph vs. etcd vs. JanusGraph vs. Transbase

System Properties Comparison Dgraph vs. etcd vs. JanusGraph vs. Transbase

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Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

A distributed reliable key-value store

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

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

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	7.25
Rank	#54	Overall
	#5	Key-value stores

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

dgraph.io

etcd.io
github.com/etcd-io/etcd

janusgraph.org

www.transaction.de/en/products/transbase.html

Technical documentation

dgraph.io/docs

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

docs.janusgraph.org

www.transaction.de/en/products/transbase/features.html

Developer

Dgraph Labs, Inc.

Linux Foundation; originally developed as Titan by Aurelius

Transaction Software GmbH

Initial release

2016

2017

1987

Current release

3.4, August 2019

0.6.3, February 2023

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

free development 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

Java

C and C++

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
Windows

experimental

Linux
OS X
Unix
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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

yes

SQL

Support of SQL

yes

APIs and other access methods

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

gRPC
JSON over HTTP

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

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

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

Clojure
Java
Python

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes, watching key changes

yes

Partitioning methods

Methods for storing different data on different nodes

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

Planned for future releases

User authentification and security via Rexster Graph Server

fine grained access rights according to SQL-standard

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More resources

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