DBMS > Manticore Search vs. Netezza vs. NSDb vs. Snowflake

System Properties Comparison Manticore Search vs. Netezza vs. NSDb vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

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

Data warehouse and analytics appliance part of IBM PureSystems

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

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	0.29
Rank	#302	Overall
	#21	Search engines

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

manticoresearch.com

www.ibm.com/products/netezza

nsdb.io

www.snowflake.com

Technical documentation

manual.manticoresearch.com

nsdb.io/Architecture

docs.snowflake.net/manuals/index.html

Developer

Manticore Software

IBM

Snowflake Computing Inc.

Initial release

2017

2000

2017

2014

Current release

6.0, February 2023

License

Commercial or Open Source

Open Source

GPL version 2

commercial

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java, Scala

Server operating systems

FreeBSD
Linux
macOS
Windows

Linux

included in appliance

Linux
macOS

hosted

Data scheme

Fixed schema

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

yes: int, bigint, decimal, string

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

all fields are automatically indexed

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

JDBC
ODBC
OLE DB

gRPC
HTTP REST
WebSocket

CLI Client
JDBC
ODBC

Supported programming languages

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

C
C++
Fortran
Java
Lua
Perl
Python
R

Java
Scala

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

yes

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

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication based on Galera library

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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

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

Using Apache Lucene

yes

In-memory capabilities

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

User concepts

Access control

Users with fine-grained authorization concept

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

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