DBMS > Amazon Redshift vs. Citus vs. Hive vs. Ignite vs. RavenDB

System Properties Comparison Amazon Redshift vs. Citus vs. Hive vs. Ignite vs. RavenDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

data warehouse software for querying and managing large distributed datasets, built on Hadoop

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.

Open Source Operational and Transactional Enterprise NoSQL Document Database

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Document store

Secondary database models

Document store

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	2.15
Rank	#117	Overall
	#56	Relational DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	3.11
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	2.84
Rank	#101	Overall
	#18	Document stores

Website

aws.amazon.com/redshift

Technical documentation

docs.aws.amazon.com/redshift

docs.citusdata.com

cwiki.apache.org/confluence/display/Hive/Home

apacheignite.readme.io/docs

ravendb.net/docs

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

initially developed by Facebook

Apache Software Foundation

Hibernating Rhinos

Initial release

2012

2010

2012

2015

2010

Current release

8.1, December 2018

3.1.3, April 2022

Apache Ignite 2.6

5.4, July 2022

License

Commercial or Open Source

commercial

Open Source

AGPL, commercial license also available

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

AGPL version 3, commercial license available

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++, Java, .Net

Server operating systems

hosted

Linux

All OS with a Java VM

Linux
OS X
Solaris
Windows

Linux
macOS
Raspberry Pi
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

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

specific XML type available, but no XML query functionality

yes

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

standard, with numerous extensions

SQL-like DML and DDL statements

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

SQL-like query language (RQL)

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
ODBC
Thrift

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

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C++
Java
PHP
Python

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

user defined functions and integration of map-reduce

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

yes

Triggers

yes

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

other methods possible by using 3rd party extensions

selectable replication factor

yes (replicated cache)

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes (compute grid and hadoop accelerator)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

Concurrency

Support for concurrent manipulation of data

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

Security Hooks for custom implementations

Authorization levels configured per client per database

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.