DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Amazon DynamoDB vs. Google Cloud Datastore vs. IBM Cloudant vs. TigerGraph

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Amazon DynamoDB vs. Google Cloud Datastore vs. IBM Cloudant vs. TigerGraph

Editorial information provided by DB-Engines

Name

Description

An online MPP (Massively Parallel Processing) data warehousing service based on Greenplum

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

Database as a Service offering based on Apache CouchDB

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Relational DBMS

Document store
Key-value store

Document store

Graph DBMS

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

Score	0.68
Rank	#231	Overall
	#105	Relational DBMS

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

aws.amazon.com/dynamodb

cloud.google.com/datastore

www.ibm.com/products/cloudant

www.tigergraph.com

Technical documentation

www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/product-introduction-overview

docs.aws.amazon.com/dynamodb

cloud.google.com/datastore/docs

cloud.ibm.com/docs/Cloudant

docs.tigergraph.com

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Amazon

Google

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Initial release

2016

2012

2008

2010

2017

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

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

Erlang

C++

Server operating systems

hosted

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, details here

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

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language (GQL)

SQL-like query language (GSQL)

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

RESTful HTTP/JSON API

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

C
Java
Perl
Python
R

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

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

C#
Java
JavaScript
Objective-C
PHP
Ruby

C++
Java

Server-side scripts

Stored procedures

yes

using Google App Engine

View functions (Map-Reduce) in JavaScript

yes

Triggers

yes

by integration with AWS Lambda

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Multi-source replication using Paxos

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

using Google Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Eventual Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Relationships in graphs

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

atomic operations within a document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

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.

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

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

Access rights for users can be defined per database

Role-based access control

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