DBMS > EsgynDB vs. Manticore Search vs. PouchDB vs. Riak TS

System Properties Comparison EsgynDB vs. Manticore Search vs. PouchDB vs. Riak TS

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Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

JavaScript DBMS with an API inspired by CouchDB

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

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	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Website

www.esgyn.cn

manticoresearch.com

pouchdb.com

Technical documentation

manual.manticoresearch.com

pouchdb.com/guides

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Esgyn

Manticore Software

Apache Software Foundation

Open Source, formerly Basho Technologies

Initial release

2015

2017

2012

2015

Current release

6.0, February 2023

7.1.1, June 2019

3.0.0, September 2022

License

Commercial or Open Source

commercial

Open Source

GPL version 2

Open Source

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++, Java

C++

JavaScript

Erlang

Server operating systems

Linux

FreeBSD
Linux
macOS
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Linux
OS X

Data scheme

yes

Fixed schema

schema-free

Typing

predefined data types such as float or date

yes

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

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

via views

restricted

SQL

Support of SQL

yes

SQL-like query language

yes, limited

APIs and other access methods

ADO.NET
JDBC
ODBC

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

HTTP REST

only for PouchDB Server
JavaScript API

HTTP API
Native Erlang Interface

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

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

JavaScript

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

View functions in JavaScript

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding

with a proxy-based framework, named couchdb-lounge

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Synchronous replication based on Galera library

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

yes

isolated transactions for atomic changes and binary logging for safe writes

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 IndexedDB, WebSQL or LevelDB as backend

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

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

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