DBMS > Bangdb vs. Firebase Realtime Database vs. Hawkular Metrics vs. HugeGraph vs. Memgraph

System Properties Comparison Bangdb vs. Firebase Realtime Database vs. Hawkular Metrics vs. HugeGraph vs. Memgraph

Editorial information provided by DB-Engines

Name

Description

Converged and high performance database for device data, events, time series, document and graph

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

A fast-speed and highly-scalable Graph DBMS

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

Primary database model

Document store
Graph DBMS
Time Series DBMS

Document store

Time Series DBMS

Graph DBMS

Secondary database models

Spatial DBMS

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	3.02
Rank	#98	Overall
	#8	Graph DBMS

Website

bangdb.com

firebase.google.com/products/realtime-database

www.hawkular.org

github.com/hugegraph
hugegraph.apache.org

memgraph.com

Technical documentation

docs.bangdb.com

firebase.google.com/docs/database

www.hawkular.org/hawkular-metrics/docs/user-guide

hugegraph.apache.org/docs

memgraph.com/docs

Social network pages

Developer

Sachin Sinha, BangDB

Google

acquired by Google 2014

Community supported by Red Hat

Baidu

Memgraph Ltd

Initial release

2012

2014

2018

2017

Current release

BangDB 2.0, October 2021

0.9

License

Commercial or Open Source

Open Source

BSD 3

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

BSL 1.1; commercial license for enterprise edition available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++

Java

C and C++

Server operating systems

Linux

hosted

Linux
OS X
Windows

Linux
macOS
Unix

Linux

Data scheme

schema-free

yes

schema-free and schema-optional

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

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

secondary, composite, nested, reverse, geospatial

yes

also supports composite index and range index

SQL

Support of SQL

SQL like support with command line tool

APIs and other access methods

Proprietary protocol
RESTful HTTP API

Android
iOS
JavaScript API
RESTful HTTP API

HTTP REST

Java API
RESTful HTTP API
TinkerPop Gremlin

Bolt protocol
Cypher query language

Supported programming languages

C
C#
C++
Java
Python

Java
JavaScript
Objective-C

Go
Java
Python
Ruby

Groovy
Java
Python

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

Server-side scripts

Stored procedures

limited functionality with using 'rules'

asynchronous Gremlin script jobs

Triggers

yes, Notifications (with Streaming only)

Callbacks are triggered when data changes

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

based on Cassandra

yes

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

Sharding

dynamic graph partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

selectable replication factor

based on Cassandra

yes

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

Multi-source replication using RAFT

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

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

Transaction concepts

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

ACID

yes

ACID

with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

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

In-memory capabilities

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

yes, run db with in-memory only mode

yes

User concepts

Access control

yes (enterprise version only)

yes, based on authentication and database rules

Users, roles and permissions

More information provided by the system vendor

Specific characteristics

Memgraph directly connects to your streaming infrastructure so you and your team...
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Competitive advantages

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Typical application scenarios

Graph algorithms in bioinformatics Social network analysis Cryptocurrency network...
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Licensing and pricing models

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

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources

DB-Engines blog posts

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