DBMS > Amazon DocumentDB vs. Datomic vs. Manticore Search

System Properties Comparison Amazon DocumentDB vs. Datomic vs. Manticore Search

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Editorial information provided by DB-Engines

Name

Description

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

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

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

Primary database model

Document store

Relational 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	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

Website

aws.amazon.com/documentdb

www.datomic.com

manticoresearch.com

Technical documentation

aws.amazon.com/documentdb/resources

docs.datomic.com

manual.manticoresearch.com

Developer

Cognitect

Manticore Software

Initial release

2019

2012

2017

Current release

1.0.6735, June 2023

6.0, February 2023

License

Commercial or Open Source

commercial

limited edition free

Open Source

GPL version 2

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Clojure

C++

Server operating systems

hosted

All OS with a Java VM

FreeBSD
Linux
macOS
Windows

Data scheme

schema-free

yes

Fixed schema

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

SQL

Support of SQL

SQL-like query language

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

RESTful HTTP API

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

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

Clojure
Java

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

Server-side scripts

Stored procedures

yes

Transaction Functions

user defined functions

Triggers

By using transaction functions

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

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

none

But extensive use of caching in the application peers

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

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

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

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

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

recommended only for testing and development

User concepts

Access control

Access rights for users and roles

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More resources

Recent citations in the news

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