DBMS > Amazon Redshift vs. Dgraph vs. Google Cloud Bigtable vs. H2GIS vs. OrigoDB

System Properties Comparison Amazon Redshift vs. Dgraph vs. Google Cloud Bigtable vs. H2GIS vs. OrigoDB

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

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

Spatial extension of H2

A fully ACID in-memory object graph database

Primary database model

Relational DBMS

Graph DBMS

Key-value store
Wide column store

Spatial DBMS

Document store
Object oriented DBMS

Secondary database models

Relational DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	0.08
Rank	#368	Overall
	#7	Spatial DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Website

aws.amazon.com/redshift

dgraph.io

cloud.google.com/bigtable

www.h2gis.org

origodb.com

Technical documentation

docs.aws.amazon.com/redshift

dgraph.io/docs

cloud.google.com/bigtable/docs

www.h2gis.org/docs/home

origodb.com/docs

Developer

Amazon (based on PostgreSQL)

Dgraph Labs, Inc.

Google

CNRS

Robert Friberg et al

Initial release

2012

2016

2015

2013

2009

under the name LiveDB

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

LGPL 3.0

Open Source

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

Server operating systems

hosted

Linux
OS X
Windows

hosted

Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

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

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

.NET Client API
HTTP API
LINQ

Supported programming languages

All languages supporting JDBC/ODBC

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

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

Java

.Net

Server-side scripts

Stored procedures

user defined functions

in Python

yes

based on H2

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

none

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous replication via Raft

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

yes

based on H2

Source-replica replication

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)

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

depending on model

Transaction concepts

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

ACID

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

Write ahead log

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

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

yes

based on H2

Role based authorization

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