DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Google Cloud Datastore vs. Hawkular Metrics vs. Microsoft Azure Table Storage vs. OrigoDB

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Google Cloud Datastore vs. Hawkular Metrics vs. Microsoft Azure Table Storage vs. OrigoDB

Editorial information provided by DB-Engines

Name

Description

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

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

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

A Wide Column Store for rapid development using massive semi-structured datasets

A fully ACID in-memory object graph database

Primary database model

Document store
Object oriented DBMS

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

Score	0.68
Rank	#231	Overall
	#105	Relational DBMS

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

cloud.google.com/datastore

www.hawkular.org

azure.microsoft.com/en-us/services/storage/tables

origodb.com

Technical documentation

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

cloud.google.com/datastore/docs

www.hawkular.org/hawkular-metrics/docs/user-guide

origodb.com/docs

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Google

Community supported by Red Hat

Microsoft

Robert Friberg et al

Initial release

2016

2008

2014

2012

2009

under the name LiveDB

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

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

yes, details here

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.

yes

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language (GQL)

APIs and other access methods

JDBC
ODBC

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

HTTP REST

RESTful HTTP API

.NET Client API
HTTP API
LINQ

Supported programming languages

C
Java
Perl
Python
R

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

Go
Java
Python
Ruby

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

.Net

Server-side scripts

Stored procedures

yes

using Google App Engine

yes

Triggers

yes

Callbacks using the Google Apps Engine

yes

via Hawkular Alerting

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

based on Cassandra

Sharding

Implicit feature of the cloud service

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication using Paxos

selectable replication factor

based on Cassandra

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

depending on model

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

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

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

Access rights based on private key authentication or shared access signatures

Role based authorization

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