DBMS > Bangdb vs. Drizzle vs. HugeGraph vs. InfluxDB vs. Lovefield

System Properties Comparison Bangdb vs. Drizzle vs. HugeGraph vs. InfluxDB vs. Lovefield

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

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

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

A fast-speed and highly-scalable Graph DBMS

DBMS for storing time series, events and metrics

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Document store
Graph DBMS
Time Series DBMS

Secondary database models

Spatial DBMS

with GEO package

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	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Website

bangdb.com

github.com/hugegraph
hugegraph.apache.org

www.influxdata.com/products/influxdb-overview

google.github.io/lovefield

Technical documentation

docs.bangdb.com

hugegraph.apache.org/docs

docs.influxdata.com/influxdb

github.com/google/lovefield/blob/master/docs/spec_index.md

Developer

Sachin Sinha, BangDB

Drizzle project, originally started by Brian Aker

Baidu

Google

Initial release

2012

2008

2018

2013

2014

Current release

BangDB 2.0, October 2021

7.2.4, September 2012

0.9

2.7.6, April 2024

2.1.12, February 2017

License

Commercial or Open Source

Open Source

BSD 3

Open Source

GNU GPL

Open Source

Apache Version 2.0

Open Source

MIT-License; commercial enterprise version available

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

C, C++

C++

Java

JavaScript

Server operating systems

Linux

FreeBSD
Linux
OS X

Linux
macOS
Unix

Linux
OS X

through Homebrew

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

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

yes

Numeric data and Strings

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

yes

SQL

Support of SQL

SQL like support with command line tool

yes

with proprietary extensions

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

Proprietary protocol
RESTful HTTP API

JDBC

Java API
RESTful HTTP API
TinkerPop Gremlin

HTTP API
JSON over UDP

Supported programming languages

C
C#
C++
Java
Python

C
C++
Java
PHP

Groovy
Java
Python

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

JavaScript

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

Triggers

yes, Notifications (with Streaming only)

hooks for callbacks inside the server can be used.

Using read-only observers

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

yes

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

Sharding

in enterprise version only

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication
Source-replica replication

yes

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

selectable replication factor

in enterprise version only

none

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

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

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

Depending on used storage engine

yes

using MemoryDB

User concepts

Access control

yes (enterprise version only)

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Users, roles and permissions

simple rights management via user accounts

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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