DBMS > Manticore Search vs. Microsoft Azure SQL Database vs. NSDb vs. OpenSearch vs. OrigoDB

System Properties Comparison Manticore Search vs. Microsoft Azure SQL Database vs. NSDb vs. OpenSearch vs. OrigoDB

Editorial information provided by DB-Engines

Name

Description

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

Database as a Service offering with high compatibility to Microsoft SQL Server

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

A distributed, RESTful search and analytics engine forked from Elasticsearch and based on Apache Lucene

A fully ACID in-memory object graph database

Primary database model

Document store
Object oriented DBMS

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Document store
Graph DBMS
Spatial DBMS

Vector DBMS

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

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	16.36
Rank	#37	Overall
	#4	Search engines

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

Website

manticoresearch.com

azure.microsoft.com/en-us/products/azure-sql/database

nsdb.io

github.com/opensearch-project
opensearch.org

origodb.com

Technical documentation

manual.manticoresearch.com

docs.microsoft.com/en-us/azure/azure-sql

nsdb.io/Architecture

opensearch.org/docs/latest

origodb.com/docs

Developer

Manticore Software

Microsoft

Amazon Web Services

Robert Friberg et al

Initial release

2017

2010

2017

2021

2009

under the name LiveDB

Current release

6.0, February 2023

V12

2.5.0, January 2023

License

Commercial or Open Source

Open Source

GPL version 2

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Open Source

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.

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Implementation language

C++

Java, Scala

Java

Server operating systems

FreeBSD
Linux
macOS
Windows

hosted

Linux
macOS

All OS with a Java VM

Linux
Windows

Data scheme

Fixed schema

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

yes

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

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

yes

can be achieved using .NET

Secondary indexes

yes

full-text index on all search fields

yes

all fields are automatically indexed

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-like query language

APIs and other access methods

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

ADO.NET
JDBC
ODBC

gRPC
HTTP REST
WebSocket

Java API
RESTful HTTP/JSON API

.NET Client API
HTTP API
LINQ

Supported programming languages

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

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

Java
Scala

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

.Net

Server-side scripts

Stored procedures

user defined functions

Transact SQL

yes

Triggers

yes

by using the 'percolation' feature

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication based on Galera library

yes, with always 3 replicas available

yes

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

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Foreign keys

Referential integrity

yes

depending on model

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

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

Role based authorization

More information provided by the system vendor

Specific characteristics

OpenSearch is a highly scalable and extensible open-source software suite for search,...
» more

Competitive advantages

Distributed as fully open source under Apache License, Version 2.0 (ALv2), OpenSearch...
» more

Typical application scenarios

The OpenSearch platform is used across a broad range of search , analytics, and observability...
» more

Licensing and pricing models

The OpenSearch Project offers open source software licensed under Apache License...
» more

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