DBMS > Amazon Redshift vs. Apache Impala vs. CouchDB vs. EJDB vs. Ignite

System Properties Comparison Amazon Redshift vs. Apache Impala vs. CouchDB vs. EJDB vs. Ignite

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Analytic DBMS for Hadoop

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

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

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Primary database model

Relational DBMS

Document store

Key-value store
Relational DBMS

Secondary database models

Document store

Spatial DBMS

using the Geocouch extension

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Website

aws.amazon.com/redshift

impala.apache.org

couchdb.apache.org

github.com/Softmotions/ejdb

ignite.apache.org

Technical documentation

docs.aws.amazon.com/redshift

impala.apache.org/impala-docs.html

docs.couchdb.org/en/stable

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

apacheignite.readme.io/docs

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Softmotions

Apache Software Foundation

Initial release

2012

2013

2005

2012

2015

Current release

4.1.0, June 2022

3.3.3, December 2023

Apache Ignite 2.6

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Apache version 2

Open Source

GPLv2

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Erlang

C++, Java, .Net

Server operating systems

hosted

Linux

Android
BSD
Linux
OS X
Solaris
Windows

server-less

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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.

yes

Secondary indexes

restricted

yes

via views

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like DML and DDL statements

ANSI-99 for query and DML statements, subset of DDL

APIs and other access methods

JDBC
ODBC

RESTful HTTP/JSON API

in-process shared library

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

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

C#
C++
Java
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

user defined functions

in Python

yes

user defined functions and integration of map-reduce

View functions in JavaScript

yes (compute grid and cache interceptors can be used instead)

Triggers

yes

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Multi-source replication
Source-replica replication

none

yes (replicated cache)

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

ACID

atomic operations within a single document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

Read/Write Locking

yes

Durability

Support for making data persistent

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Access rights for users can be defined per database

Security Hooks for custom implementations

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