DBMS > Altibase vs. DataFS vs. Drizzle vs. Manticore Search vs. OrigoDB

System Properties Comparison Altibase vs. DataFS vs. Drizzle vs. Manticore Search vs. OrigoDB

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 enterprise grade, high-performance RDBMS

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

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

Multi-storage database for search, including full-text search.

A fully ACID in-memory object graph database

Primary database model

Document store
Object oriented DBMS

Secondary database models

Graph DBMS

Time Series DBMS

using the Manticore Columnar Library

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

Score	1.07
Rank	#186	Overall
	#87	Relational DBMS

Score	0.06
Rank	#354	Overall
	#15	Object oriented DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Website

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

dev.mobiland.com/Overview.xsp

manual.manticoresearch.com

origodb.com/docs

Developer

Altibase

Mobiland AG

Drizzle project, originally started by Brian Aker

Manticore Software

Robert Friberg et al

Initial release

1999

2018

2008

2017

2009

under the name LiveDB

Current release

v7.3, 2023, August 2023

1.1.263, October 2022

7.2.4, September 2012

6.0, February 2023

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

commercial

Open Source

GNU GPL

Open Source

GPL version 2

Open Source

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++

Server operating systems

AIX
HP-UX
Linux

Windows

FreeBSD
Linux
OS X

FreeBSD
Linux
macOS
Windows

Linux
Windows

Data scheme

yes

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

Fixed schema

yes

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

User defined using .NET types and collections

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.

Can index from XML

can be achieved using .NET

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

ANSI SQL-92

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

JDBC
ODBC
Proprietary protocol

.NET Client API
Proprietary client DLL
WinRT client

JDBC

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

.NET Client API
HTTP API
LINQ

Supported programming languages

C
C++
Java

.Net
C
C#
C++
VB.Net

C
C++
Java
PHP

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

.Net

Server-side scripts

Stored procedures

stored procedures and stored functions

user defined functions

yes

Triggers

yes

no, except callback-events from server when changes happened

hooks for callbacks inside the server can be used.

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Proprietary Sharding system

Sharding

Partitioning is done manually, search queries against distributed index is supported

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

Synchronous replication based on Galera library

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

depending on model

Transaction concepts

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

ACID

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Manticore index.

yes

Write ahead log

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Windows-Profile

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Role based authorization

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