DBMS > Badger vs. Drizzle vs. EJDB vs. Faircom DB vs. Oracle Coherence

System Properties Comparison Badger vs. Drizzle vs. EJDB vs. Faircom DB vs. Oracle Coherence

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

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

Oracles in-memory data grid solution

Primary database model

Key-value store

Relational DBMS

Document store

Key-value store
Relational DBMS

Key-value store

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

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	0.20
Rank	#318	Overall
	#48	Key-value stores
	#141	Relational DBMS

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Website

github.com/dgraph-io/badger

github.com/Softmotions/ejdb

www.faircom.com/products/faircom-db

www.oracle.com/java/coherence

Technical documentation

godoc.org/github.com/dgraph-io/badger

github.com/Softmotions/ejdb/blob/master/README.md

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

docs.oracle.com/en/middleware/standalone/coherence

Developer

DGraph Labs

Drizzle project, originally started by Brian Aker

Softmotions

FairCom Corporation

Oracle

Initial release

2017

2008

2012

1979

2007

Current release

7.2.4, September 2012

V12, November 2020

14.1, August 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GNU GPL

Open Source

GPLv2

commercial

Restricted, free version available

commercial

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++

ANSI C, C++

Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
OS X

server-less

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

All OS with a Java VM

Data scheme

schema-free

yes

schema-free

schema free, schema optional, schema required, partial schema,

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes, ANSI SQL Types, JSON, typed binary structures

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

SQL

Support of SQL

yes

with proprietary extensions

yes, ANSI SQL with proprietary extensions

APIs and other access methods

JDBC

in-process shared library

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

JCache
JPA
RESTful HTTP API

Supported programming languages

C
C++
Java
PHP

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

.Net
C++
Java

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

Triggers

hooks for callbacks inside the server can be used.

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

none

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

ACID

tunable from ACID to Eventually Consistent

configurable

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

Yes, tunable from durable to delayed durability to in-memory

yes

optionally

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

Fine grained access rights according to SQL-standard with additional protections for files

authentification to access the cache via certificates or http basic authentication

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