DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Google BigQuery vs. Google Cloud Spanner vs. Microsoft Azure Synapse Analytics vs. WakandaDB

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Google BigQuery vs. Google Cloud Spanner vs. Microsoft Azure Synapse Analytics vs. WakandaDB

Editorial information provided by DB-Engines

Name

Description

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

Large scale data warehouse service with append-only tables

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Relational DBMS

Object oriented DBMS

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

Score	0.76
Rank	#220	Overall
	#102	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	2.84
Rank	#100	Overall
	#51	Relational DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	0.10
Rank	#356	Overall
	#17	Object oriented DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

cloud.google.com/bigquery

cloud.google.com/spanner

azure.microsoft.com/services/synapse-analytics

wakanda.github.io

Technical documentation

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

cloud.google.com/bigquery/docs

cloud.google.com/spanner/docs

docs.microsoft.com/azure/synapse-analytics

wakanda.github.io/doc

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Google

Microsoft

Wakanda SAS

Initial release

2016

2010

2017

2016

2012

Current release

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Open Source

AGPLv3, extended commercial license available

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

C++

C++, JavaScript

Server operating systems

hosted

Linux
OS X
Windows

Data scheme

yes

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

Query statements complying to ANSI 2011

yes

APIs and other access methods

JDBC
ODBC

RESTful HTTP/JSON API

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

ADO.NET
JDBC
ODBC

RESTful HTTP API

Supported programming languages

C
Java
Perl
Python
R

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Go
Java
JavaScript (Node.js)
Python

C#
Java
PHP

JavaScript

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

Transact SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Sharding

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication with 3 replicas for regional instances.

yes

none

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

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

Strict serializable isolation

ACID

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.

User concepts

Access control

fine grained access rights according to SQL-standard

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

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

yes

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