DBMS > Manticore Search vs. Memcached vs. Microsoft Azure Cosmos DB vs. STSdb

System Properties Comparison Manticore Search vs. Memcached vs. Microsoft Azure Cosmos DB vs. STSdb

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

In-memory key-value store, originally intended for caching

Globally distributed, horizontally scalable, multi-model database service

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Search engine

Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Key-value store

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	0.29
Rank	#302	Overall
	#21	Search engines

Score	18.08
Rank	#32	Overall
	#4	Key-value stores

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

manticoresearch.com

www.memcached.org

azure.microsoft.com/services/cosmos-db

github.com/STSSoft/STSdb4

Technical documentation

manual.manticoresearch.com

github.com/memcached/memcached/wiki

learn.microsoft.com/azure/cosmos-db

Developer

Manticore Software

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Microsoft

STS Soft SC

Initial release

2017

2003

2014

2011

Current release

6.0, February 2023

1.6.27, May 2024

4.0.8, September 2015

License

Commercial or Open Source

Open Source

GPL version 2

Open Source

BSD license

commercial

Open Source

GPLv2, commercial license available

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

FreeBSD
Linux
OS X
Unix
Windows

hosted

Windows

Data scheme

Fixed schema

schema-free

yes

Typing

predefined data types such as float or date

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

yes

JSON types

yes

primitive types and user defined types (classes)

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

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

Proprietary protocol

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

.NET Client API

Supported programming languages

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

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

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

C#
Java

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

none

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication based on Galera library

none

Repcached, a Memcached patch, provides this functionallity

yes

Implicit feature of the cloud service

none

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

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

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

User concepts

Access control

yes

using SASL (Simple Authentication and Security Layer) protocol

Access rights can be defined down to the item level

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.