DBMS > Blueflood vs. Drizzle vs. HugeGraph vs. Memgraph vs. NebulaGraph

System Properties Comparison Blueflood vs. Drizzle vs. HugeGraph vs. Memgraph vs. NebulaGraph

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.

Description

Scalable TimeSeries DBMS based on Cassandra

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

A fast-speed and highly-scalable Graph DBMS

An open source graph database built for real-time streaming and compatible with Neo4j

A distributed, linear scalable, high perfomant Graph DBMS

Primary database model

Time Series DBMS

Relational DBMS

Graph DBMS

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

Score	0.09
Rank	#353	Overall
	#33	Time Series DBMS

Score	0.15
Rank	#339	Overall
	#33	Graph DBMS

Score	3.00
Rank	#102	Overall
	#8	Graph DBMS

Score	2.12
Rank	#125	Overall
	#10	Graph DBMS

Website

blueflood.io

github.com/hugegraph
hugegraph.apache.org

memgraph.com

github.com/vesoft-inc/nebula
www.nebula-graph.io

Technical documentation

github.com/rax-maas/blueflood/wiki

hugegraph.apache.org/docs

memgraph.com/docs

docs.nebula-graph.io

Social network pages

Developer

Rackspace

Drizzle project, originally started by Brian Aker

Baidu

Memgraph Ltd

Vesoft Inc.

Initial release

2013

2008

2018

2017

2019

Current release

7.2.4, September 2012

0.9

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GNU GPL

Open Source

Apache Version 2.0

commercial

Free license available

Open Source

Apache Version 2.0 + Common Clause 1.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Java

C and C++

C++

Server operating systems

Linux
OS X

FreeBSD
Linux
OS X

Linux
macOS
Unix

Linux

Data scheme

predefined scheme

yes

schema-free and schema-optional

Strong typed schema

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

also supports composite index and range index

yes

Nebula Graph internally uses the Key-Value store RocksDB for persistency. The vertices, edges, and their properties are stored as Key while their values are stored as Value. The primary indexes are per Key and secondary indexes are per Value.

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

HTTP REST

JDBC

Java API
RESTful HTTP API
TinkerPop Gremlin

Bolt protocol
Cypher query language

Browser interface
console (shell)
Cypher Query Language
GO Object Graph Mapper
Java Object Graph Mapper
NGBatis

ORM framework for NebulaGraph and Spring-Boot
Proprietary native API
Python Object Graph Mapper
Query language nGQL

Supported programming languages

C
C++
Java
PHP

Groovy
Java
Python

.Net
C
C++
Elixir
Go
Haskell
Java
JavaScript
PHP
Python
Ruby
Scala

.Net
C++
Go
Java
PHP
Python

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

user defined functions

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

dynamic graph partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

yes

depending on used storage backend, e.g. Cassandra and HBase

Multi-source replication using RAFT

Causal Clustering using Raft protocol

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

relationships in graphs

yes

Relationships in graphs

Transaction concepts

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

ACID

with snapshot isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

with periodic snapshot and write-ahead logging (WAL) of changes

yes

using RocksDB

In-memory capabilities

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

yes

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Users, roles and permissions

Role-based access control

More information provided by the system vendor

Specific characteristics

Memgraph directly connects to your streaming infrastructure so you and your team...
» more

NebulaGraph is a truly distributed, linearly scalable, lightning-fast graph database,...
» more

Competitive advantages

Business Source License ensures a future for the Memgraph community MAGE algorithm...
» more

NebulaGraph boasts the world's only graph database solution that is able to host...
» more

Typical application scenarios

Graph algorithms in bioinformatics Social network analysis Cryptocurrency network...
» more

Social networking Fraud detection Knowledge graph Data warehouse management Anti...
» more

Key customers

Companies from a variety of industries have implemented NebulaGraph Database in production,...
» more

Market metrics

At our very early stage, NebulaGraph has already received over 10,000 stars on GitHub...
» more

Licensing and pricing models

You can check out our pricing model and licenses on the company website .
» more

NebulaGraph is open source and free to use under Apache 2.0 license.
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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