DBMS > Amazon Redshift vs. GridGain vs. Postgres-XL vs. RocksDB vs. Sadas Engine

System Properties Comparison Amazon Redshift vs. GridGain vs. Postgres-XL vs. RocksDB vs. Sadas Engine

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

GridGain is an in-memory computing platform, built on Apache Ignite

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Website

aws.amazon.com/redshift

Technical documentation

docs.aws.amazon.com/redshift

www.gridgain.com/docs/index.html

www.postgres-xl.org/documentation

github.com/facebook/rocksdb/wiki

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Amazon (based on PostgreSQL)

GridGain Systems, Inc.

Facebook, Inc.

SADAS s.r.l.

Initial release

2012

2007

2014

since 2012, originally named StormDB

2013

2006

Current release

GridGain 8.5.1

10 R1, October 2018

9.2.1, May 2024

8.0

License

Commercial or Open Source

commercial

Open Source

Mozilla public license

Open Source

BSD

commercial

free trial version 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++, .Net

C++

Server operating systems

hosted

Linux
OS X
Solaris
Windows

Linux
macOS

Linux

AIX
Linux
Windows

Data scheme

yes

schema-free

yes

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

XML type, but no XML query functionality

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

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

yes

distributed, parallel query execution

yes

APIs and other access methods

JDBC
ODBC

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

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

C++ API
Java API

JDBC
ODBC
Proprietary protocol

Supported programming languages

All languages supporting JDBC/ODBC

C#
C++
Java
PHP
Python
Ruby
Scala

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

C
C++
Go
Java
Perl
Python
Ruby

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in Python

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

user defined functions

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes (replicated cache)

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

MVCC

yes

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

managed by 'Learn by Usage'

User concepts

Access control

fine grained access rights according to SQL-standard

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

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