DBMS > AllegroGraph vs. Badger vs. Couchbase vs. Drizzle

System Properties Comparison AllegroGraph vs. Badger vs. Couchbase vs. Drizzle

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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

High performance, persistent RDF store with additional support for Graph DBMS

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

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

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

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Key-value store

Document store

Relational DBMS

Secondary database models

Spatial DBMS

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

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

Score	1.06
Rank	#187	Overall
	#30	Document stores
	#17	Graph DBMS
	#7	RDF stores
	#7	Vector DBMS

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

Score	17.30
Rank	#36	Overall
	#5	Document stores

Website

allegrograph.com

github.com/dgraph-io/badger

www.couchbase.com

Technical documentation

franz.com/agraph/support/documentation/current/agraph-introduction.html

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

docs.couchbase.com

Developer

Franz Inc.

DGraph Labs

Couchbase, Inc.

Drizzle project, originally started by Brian Aker

Initial release

2004

2017

2011

2008

Current release

8.0, December 2023

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

7.2.4, September 2012

License

Commercial or Open Source

commercial

Limited community edition free

Open Source

Apache 2.0

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

GNU GPL

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++, Go and Erlang

C++

Server operating systems

Linux
OS X
Windows

BSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

FreeBSD
Linux
OS X

Data scheme

yes

RDF schemas

schema-free

yes

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.

bulk load of XML files possible

Secondary indexes

yes

SQL

Support of SQL

SPARQL is used as query language

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

yes

with proprietary extensions

APIs and other access methods

RESTful HTTP API
SPARQL

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

JDBC

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

C
C++
Java
PHP

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

Triggers

yes

via the TAP protocol

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

with Federation

none

Automatic Sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

Multi-source replication

including cross data center replication
Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

none

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

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

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

Ephemeral buckets

User concepts

Access control

Users with fine-grained authorization concept, user roles and pluggable authentication

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Pluggable authentication mechanisms

e.g. LDAP, HTTP

More information provided by the system vendor

Specific characteristics

Knowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
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Competitive advantages

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