DBMS > Manticore Search vs. Microsoft Azure Table Storage vs. Oracle Rdb vs. Quasardb vs. Snowflake

System Properties Comparison Manticore Search vs. Microsoft Azure Table Storage vs. Oracle Rdb vs. Quasardb vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

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

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

Distributed, high-performance timeseries database

Cloud-based data warehousing service for structured and semi-structured data

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	0.23
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

Score	0.13
Rank	#332	Overall
	#28	Time Series DBMS

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Website

manticoresearch.com

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

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

quasar.ai

www.snowflake.com

Technical documentation

manual.manticoresearch.com

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

doc.quasar.ai/master

docs.snowflake.net/manuals/index.html

Developer

Manticore Software

Microsoft

Oracle, originally developed by Digital Equipment Corporation (DEC)

quasardb

Snowflake Computing Inc.

Initial release

2017

2012

1984

2009

2014

Current release

6.0, February 2023

7.4.1.1, 2021

3.14.1, January 2024

License

Commercial or Open Source

Open Source

GPL version 2

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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
macOS
Windows

hosted

HP Open VMS

BSD
Linux
OS X
Windows

hosted

Data scheme

Fixed schema

schema-free

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

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

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

yes

integer and binary

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

yes

Secondary indexes

yes

full-text index on all search fields

yes

with tags

SQL

Support of SQL

SQL-like query language

yes

SQL-like query language

yes

APIs and other access methods

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

RESTful HTTP API

HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

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

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

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding

Implicit feature of the cloud service

Sharding

consistent hashing

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication based on Galera library

yes

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

Source-replica replication with selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

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

yes

isolated transactions for atomic changes and binary logging for safe writes

optimistic locking

yes, on a single node

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

by using LevelDB

yes

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

Access rights based on private key authentication or shared access signatures

Cryptographically strong user authentication and audit trail

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

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