DBMS > Manticore Search vs. Microsoft Azure Cosmos DB vs. Sequoiadb vs. Typesense

System Properties Comparison Manticore Search vs. Microsoft Azure Cosmos DB vs. Sequoiadb vs. Typesense

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Editorial information provided by DB-Engines

Name

Description

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

Globally distributed, horizontally scalable, multi-model database service

NewSQL database with distributed OLTP and SQL

A typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity

Primary database model

Search engine

Document store
Graph DBMS
Key-value store
Wide column store

Document store
Relational DBMS

Search engine

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Spatial DBMS

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

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Score	0.79
Rank	#210	Overall
	#14	Search engines

Website

manticoresearch.com

azure.microsoft.com/services/cosmos-db

www.sequoiadb.com

typesense.org

Technical documentation

manual.manticoresearch.com

learn.microsoft.com/azure/cosmos-db

www.sequoiadb.com/en/index.php?m=Files&a=index

typesense.org/docs

Developer

Manticore Software

Microsoft

Sequoiadb Ltd.

Initial release

2017

2014

2013

2015

Current release

6.0, February 2023

License

Commercial or Open Source

Open Source

GPL version 2

commercial

Open Source

Server: AGPL; Client: Apache V2

Open Source

GPL V3

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

Linux

Data scheme

Fixed schema

schema-free

pre-defined schema optional

Typing

predefined data types such as float or date

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

yes

JSON types

yes

oid, date, timestamp, binary, regex

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

full-text index on all search fields

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

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

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

proprietary protocol using JSON

RESTful HTTP API

Supported programming languages

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

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

.Net
C++
Java
PHP
Python

.Net

community maintained
Clojure

community maintained
Dart

community maintained
Go

community maintained
Java

community maintained
JavaScript
Perl

community maintained
PHP
Python
Ruby
Rust

community maintained
Swift

community maintained

Server-side scripts

Stored procedures

user defined functions

JavaScript

Triggers

JavaScript

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

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication based on Galera library

yes

Implicit feature of the cloud service

Source-replica replication

Multi-source replication using RAFT

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency

Foreign keys

Referential integrity

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

Multi-item ACID transactions with snapshot isolation within a partition

Document is locked during a transaction

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

Access rights can be defined down to the item level

simple password-based access control

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