DBMS > Amazon Redshift vs. Graph Engine vs. HBase vs. Memgraph vs. Riak KV

System Properties Comparison Amazon Redshift vs. Graph Engine vs. HBase vs. Memgraph vs. Riak KV

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Wide-column store based on Apache Hadoop and on concepts of BigTable

An open source graph database built for real-time streaming and compatible with Neo4j

Distributed, fault tolerant key-value store

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Wide column store

Graph DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	3.02
Rank	#98	Overall
	#8	Graph DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Website

aws.amazon.com/redshift

www.graphengine.io

hbase.apache.org

memgraph.com

Technical documentation

docs.aws.amazon.com/redshift

www.graphengine.io/docs/manual

hbase.apache.org/book.html

memgraph.com/docs

www.tiot.jp/riak-docs/riak/kv/latest

Social network pages

Developer

Amazon (based on PostgreSQL)

Microsoft

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Memgraph Ltd

OpenSource, formerly Basho Technologies

Initial release

2012

2010

2008

2017

2009

Current release

2.3.4, January 2021

3.2.0, December 2022

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

Apache version 2

Open Source

BSL 1.1; commercial license for enterprise edition available

Open Source

Apache version 2, commercial enterprise edition

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

.NET and C

Java

C and C++

Erlang

Server operating systems

hosted

.NET

Linux
Unix
Windows

using Cygwin

Linux

Linux
OS X

Data scheme

yes

schema-free, schema definition possible

schema-free and schema-optional

schema-free

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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.

Secondary indexes

restricted

SQL

Support of SQL

yes

does not fully support an SQL-standard

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

Java API
RESTful HTTP API
Thrift

Bolt protocol
Cypher query language

HTTP API
Native Erlang Interface

Supported programming languages

All languages supporting JDBC/ODBC

C#
C++
F#
Visual Basic

C
C#
C++
Groovy
Java
PHP
Python
Scala

.Net
C
C++
Elixir
Go
Haskell
Java
JavaScript
PHP
Python
Ruby
Scala

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Coprocessors in Java

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

dynamic graph partitioning

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

Multi-source replication using RAFT

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

relationships in graphs

links between data sets can be stored

Transaction concepts

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

ACID

Single row ACID (across millions of columns)

ACID

with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

with periodic snapshot and write-ahead logging (WAL) of changes

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 Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

Users, roles and permissions

yes, using Riak Security

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

Graph algorithms in bioinformatics Social network analysis Cryptocurrency network...
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Licensing and pricing models

You can check out our pricing model and licenses on the company website .
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