DBMS > Amazon DocumentDB vs. Apache Impala vs. EJDB vs. Manticore Search vs. Newts

System Properties Comparison Amazon DocumentDB vs. Apache Impala vs. EJDB vs. Manticore Search vs. Newts

Editorial information provided by DB-Engines

Name

Description

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

Analytic DBMS for Hadoop

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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

Time Series DBMS based on Cassandra

Primary database model

Secondary database models

Document store

Time Series DBMS

using the Manticore Columnar Library

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

Score	1.89
Rank	#137	Overall
	#24	Document stores

Score	14.03
Rank	#40	Overall
	#24	Relational DBMS

Score	0.30
Rank	#294	Overall
	#44	Document stores

Score	0.23
Rank	#317	Overall
	#21	Search engines

Score	0.00
Rank	#396	Overall
	#42	Time Series DBMS

Website

aws.amazon.com/documentdb

impala.apache.org

github.com/Softmotions/ejdb

manticoresearch.com

opennms.github.io/newts

Technical documentation

aws.amazon.com/documentdb/resources

impala.apache.org/impala-docs.html

github.com/Softmotions/ejdb/blob/master/README.md

manual.manticoresearch.com

github.com/OpenNMS/newts/wiki

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Softmotions

Manticore Software

OpenNMS Group

Initial release

2019

2013

2012

2017

2014

Current release

4.1.0, June 2022

6.0, February 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

GPLv2

Open Source

GPL version 2

Open Source

Apache 2.0

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++

Java

Server operating systems

hosted

Linux

server-less

FreeBSD
Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

Fixed schema

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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

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

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

JDBC
ODBC

in-process shared library

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

HTTP REST
Java API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

All languages supporting JDBC/ODBC

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

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

Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

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

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

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

selectable replication factor

none

Synchronous replication based on Galera library

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

Atomic single-document operations

yes

isolated transactions for atomic changes and binary logging for safe writes

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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.

User concepts

Access control

Access rights for users and roles

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

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