DBMS > Drizzle vs. Infobright vs. Manticore Search vs. Microsoft Azure Table Storage vs. Oracle Rdb

System Properties Comparison Drizzle vs. Infobright vs. Manticore Search vs. Microsoft Azure Table Storage vs. Oracle Rdb

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

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

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

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

A Wide Column Store for rapid development using massive semi-structured datasets

Primary database model

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	0.88
Rank	#198	Overall
	#92	Relational DBMS

Score	0.23
Rank	#301	Overall
	#21	Search engines

Score	3.55
Rank	#80	Overall
	#6	Wide column stores

Score	1.04
Rank	#184	Overall
	#84	Relational DBMS

Website

ignitetech.com/softwarelibrary/infobrightdb

manticoresearch.com

azure.microsoft.com/en-us/services/storage/tables

www.oracle.com/database/technologies/related/rdb.html

Technical documentation

manual.manticoresearch.com

www.oracle.com/database/technologies/related/rdb-doc.html

Developer

Drizzle project, originally started by Brian Aker

Ignite Technologies Inc.; formerly InfoBright Inc.

Manticore Software

Microsoft

Oracle, originally developed by Digital Equipment Corporation (DEC)

Initial release

2008

2005

2017

2012

1984

Current release

7.2.4, September 2012

6.0, February 2023

7.4.1.1, 2021

License

Commercial or Open Source

Open Source

GNU GPL

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

GPL version 2

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Server operating systems

FreeBSD
Linux
OS X

Linux
Windows

FreeBSD
Linux
macOS
Windows

hosted

HP Open VMS

Data scheme

yes

Fixed schema

schema-free

Flexible Schema (defined schema, partial schema, schema free)

Typing

predefined data types such as float or date

yes

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

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.

Can index from XML

Secondary indexes

yes

Knowledge Grid Technology used instead

yes

full-text index on all search fields

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

SQL-like query language

yes

APIs and other access methods

JDBC

ADO.NET
JDBC
ODBC

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

RESTful HTTP API

Supported programming languages

C
C++
Java
PHP

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

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

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

Synchronous replication based on Galera library

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

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

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

optimistic locking

yes, on a single node

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

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

exploiting MySQL or PostgreSQL frontend capabilities

Access rights based on private key authentication or shared access signatures

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