DBMS > Dgraph vs. Drizzle vs. Hypertable vs. Kuzu vs. ToroDB

System Properties Comparison Dgraph vs. Drizzle vs. Hypertable vs. Kuzu vs. ToroDB

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Distributed and scalable native Graph DBMS

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

An open source BigTable implementation based on distributed file systems such as Hadoop

An embeddable property Graph DBMS built for query speed and scalability

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

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

Score	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	0.00
Rank	#402	Overall
	#41	Graph DBMS

Website

dgraph.io

kuzudb.com

github.com/torodb/server

Technical documentation

dgraph.io/docs

docs.kuzudb.com

Developer

Dgraph Labs, Inc.

Drizzle project, originally started by Brian Aker

Hypertable Inc.

8Kdata

Initial release

2016

2008

2009

2022

2016

Current release

7.2.4, September 2012

0.9.8.11, March 2016

0.4.2, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GNU GPL

Open Source

GNU version 3. Commercial license available

Open Source

MIT license

Open Source

AGPL-V3

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

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
OS X

Linux
OS X
Windows

an inofficial Windows port is available

server-less

All OS with a Java 7 VM

Data scheme

schema-free

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

restricted

only exact value or prefix value scans

SQL

Support of SQL

yes

with proprietary extensions

APIs and other access methods

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

JDBC

C++ API
Thrift

CLI Client
Cypher Query Language

Supported programming languages

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

C
C++
Java
PHP

C++
Java
Perl
PHP
Python
Ruby

C
C#
C++
Java
JavaScript
Python
Rust

Server-side scripts

Stored procedures

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

Multi-source replication
Source-replica replication

selectable replication factor on file system level

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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.

User concepts

Access control

Planned for future releases

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users and roles

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