DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Apache Pinot vs. Google Cloud Spanner vs. Microsoft Azure Cosmos DB vs. WakandaDB

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Apache Pinot vs. Google Cloud Spanner vs. Microsoft Azure Cosmos DB vs. WakandaDB

Editorial information provided by DB-Engines

Name

Description

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

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

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.

Globally distributed, horizontally scalable, multi-model database service

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

Document store
Graph DBMS
Key-value store
Wide column store

Object oriented DBMS

Secondary database models

Spatial DBMS

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

Score	0.79
Rank	#213	Overall
	#101	Relational DBMS

Score	0.35
Rank	#274	Overall
	#128	Relational DBMS

Score	2.69
Rank	#101	Overall
	#51	Relational DBMS

Score	24.97
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

pinot.apache.org

cloud.google.com/spanner

azure.microsoft.com/services/cosmos-db

wakanda.github.io

Technical documentation

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

docs.pinot.apache.org

cloud.google.com/spanner/docs

learn.microsoft.com/azure/cosmos-db

wakanda.github.io/doc

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Apache Software Foundation and contributors

Google

Microsoft

Wakanda SAS

Initial release

2016

2015

2017

2014

2012

Current release

1.0.0, September 2023

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

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

Java

C++, JavaScript

Server operating systems

hosted

All OS with a Java JDK11 or higher

hosted

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

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

All properties auto-indexed by default

SQL

Support of SQL

yes

SQL-like query language

yes

Query statements complying to ANSI 2011

SQL-like query language

APIs and other access methods

JDBC
ODBC

JDBC

gRPC (using protocol buffers) API
JDBC

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

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

RESTful HTTP API

Supported programming languages

C
Java
Perl
Python
R

Go
Java
Python

Go
Java
JavaScript (Node.js)
Python

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

JavaScript

Server-side scripts

Stored procedures

yes

JavaScript

yes

Triggers

yes

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning

Sharding

Implicit feature of the cloud service

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

Implicit feature of the cloud service

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

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

Transaction concepts

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

ACID

Strict serializable isolation

Multi-item ACID transactions with snapshot isolation within a partition

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

Access rights can be defined down to the item level

yes

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