DBMS > Amazon DocumentDB vs. Atos Standard Common Repository vs. JSqlDb vs. Manticore Search

System Properties Comparison Amazon DocumentDB vs. Atos Standard Common Repository vs. JSqlDb vs. Manticore Search

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Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

JavaScript Query Language Database, stores JavaScript objects and primitives

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

Primary database model

Document store

Document store
Key-value store

Document store
Object oriented DBMS

Search engine

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	0.22
Rank	#312	Overall
	#21	Search engines

Website

aws.amazon.com/documentdb

atos.net/en/convergence-creators/portfolio/standard-common-repository

jsqldb.org (offline)

manticoresearch.com

Technical documentation

aws.amazon.com/documentdb/resources

manual.manticoresearch.com

Developer

Atos Convergence Creators

Konrad von Backstrom

Manticore Software

Initial release

2019

2016

2018

2017

Current release

1703

0.8, December 2018

6.0, February 2023

License

Commercial or Open Source

commercial

Open Source

GPL version 2

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

Java

C++

Server operating systems

hosted

Linux

Linux
macOS
Windows

FreeBSD
Linux
macOS
Windows

Data scheme

schema-free

Schema and schema-less with LDAP views

schema-free

Fixed schema

Typing

predefined data types such as float or date

yes

optional

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.

yes

Can index from XML

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like query language

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

LDAP

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

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

All languages with LDAP bindings

JavaScript

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

Server-side scripts

Stored procedures

functions in JavaScript

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

cell division

none

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

yes

none

Synchronous replication based on Galera library

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

Atomic single-document operations

Atomic execution of specific operations

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

using RocksDB

yes

The original contents of fields are not stored in the Manticore index.

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 for users and roles

LDAP bind authentication

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More resources

Recent citations in the news

Use LangChain and vector search on Amazon DocumentDB to build a generative AI chatbot | Amazon Web Services
20 May 2024, AWS Blog

AWS announces Amazon DocumentDB zero-ETL integration with Amazon OpenSearch Service
16 May 2024, AWS Blog

Vector search for Amazon DocumentDB (with MongoDB compatibility) is now generally available | Amazon Web Services
29 November 2023, AWS Blog

AWS announces Amazon DocumentDB I/O-Optimized
21 November 2023, AWS Blog

Use headless clusters in Amazon DocumentDB for cost-effective multi-Region resiliency | Amazon Web Services
8 March 2024, AWS Blog

provided by Google News

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10 February 2024, Atos

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1 June 2022, hackernoon.com

8 Powerful Alternatives to Elasticsearch
25 April 2024, Insider Monkey

Manticore is a Faster Alternative to Elasticsearch in C++
25 July 2022, hackernoon.com

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1 February 2023, Gizmodo

provided by Google News

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