DBMS > Bangdb vs. Drizzle vs. H2 vs. LevelDB vs. ObjectBox

System Properties Comparison Bangdb vs. Drizzle vs. H2 vs. LevelDB vs. ObjectBox

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.

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Extremely fast embedded database for small devices, IoT and Mobile

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Key-value store

Object oriented DBMS

Secondary database models

Spatial DBMS

Time Series DBMS

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

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS

Website

bangdb.com

www.h2database.com

github.com/google/leveldb

objectbox.io

Technical documentation

docs.bangdb.com

www.h2database.com/html/main.html

github.com/google/leveldb/blob/main/doc/index.md

docs.objectbox.io

Developer

Sachin Sinha, BangDB

Drizzle project, originally started by Brian Aker

Thomas Mueller

Google

ObjectBox Limited

Initial release

2012

2008

2005

2011

2017

Current release

BangDB 2.0, October 2021

7.2.4, September 2012

2.2.220, July 2023

1.23, February 2021

License

Commercial or Open Source

Open Source

BSD 3

Open Source

GNU GPL

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

BSD

Open Source

Apache License 2.0

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, C++

C++

Java

C++

C and C++

Server operating systems

Linux

FreeBSD
Linux
OS X

All OS with a Java VM

Illumos
Linux
OS X
Windows

Android
iOS
Linux
macOS
Windows

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

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

SQL

Support of SQL

SQL like support with command line tool

yes

with proprietary extensions

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

JDBC

JDBC
ODBC

Proprietary native API

Supported programming languages

C
C#
C++
Java
Python

C
C++
Java
PHP

Java

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

Triggers

yes, Notifications (with Streaming only)

hooks for callbacks inside the server can be used.

yes

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

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

With clustering: 2 database servers on different computers operate on identical copies of a database

none

online/offline synchronization between client and server

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

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, optimistic concurrency control

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

with automatic compression on writes

yes

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)

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

yes

More information provided by the system vendor

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