DBMS > Amazon Redshift vs. Dgraph vs. EsgynDB vs. Google Cloud Bigtable vs. Memcached

System Properties Comparison Amazon Redshift vs. Dgraph vs. EsgynDB vs. Google Cloud Bigtable vs. Memcached

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Distributed and scalable native Graph DBMS

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

In-memory key-value store, originally intended for caching

Primary database model

Relational DBMS

Graph DBMS

Relational DBMS

Key-value store
Wide column store

Key-value store

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	19.42
Rank	#32	Overall
	#4	Key-value stores

Website

aws.amazon.com/redshift

dgraph.io

www.esgyn.cn

cloud.google.com/bigtable

www.memcached.org

Technical documentation

docs.aws.amazon.com/redshift

dgraph.io/docs

cloud.google.com/bigtable/docs

github.com/memcached/memcached/wiki

Developer

Amazon (based on PostgreSQL)

Dgraph Labs, Inc.

Esgyn

Google

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Initial release

2012

2016

2015

2003

Current release

1.6.25, March 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

BSD license

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++, Java

Server operating systems

hosted

Linux
OS X
Windows

Linux

hosted

FreeBSD
Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

APIs and other access methods

JDBC
ODBC

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

ADO.NET
JDBC
ODBC

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

Proprietary protocol

Supported programming languages

All languages supporting JDBC/ODBC

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

All languages supporting JDBC/ODBC/ADO.Net

C#
C++
Go
Java
JavaScript (Node.js)
Python

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

Java Stored Procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous replication via Raft

Multi-source replication between multi datacenters

Internal replication in Colossus, and regional replication between two clusters in different zones

none

Repcached, a Memcached patch, provides this functionallity

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 (for a single cluster), Eventual consistency (for two or more replicated clusters)

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

Atomic single-row operations

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

Planned for future releases

fine grained access rights according to SQL-standard

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

yes

using SASL (Simple Authentication and Security Layer) protocol

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