DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Apache Druid vs. Microsoft Azure Cosmos DB vs. Oracle Rdb vs. WakandaDB

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Apache Druid vs. Microsoft Azure Cosmos DB vs. Oracle Rdb vs. WakandaDB

Editorial information provided by DB-Engines

Name

Description

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

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

Relational DBMS
Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Object oriented DBMS

Secondary database models

Spatial DBMS

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

Score	0.76
Rank	#220	Overall
	#102	Relational DBMS

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	1.14
Rank	#178	Overall
	#80	Relational DBMS

Score	0.10
Rank	#356	Overall
	#16	Object oriented DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

druid.apache.org

azure.microsoft.com/services/cosmos-db

www.oracle.com/database/technologies/related/rdb.html

wakanda.github.io

Technical documentation

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

druid.apache.org/docs/latest/design

learn.microsoft.com/azure/cosmos-db

www.oracle.com/database/technologies/related/rdb-doc.html

wakanda.github.io/doc

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Apache Software Foundation and contributors

Microsoft

Oracle, originally developed by Digital Equipment Corporation (DEC)

Wakanda SAS

Initial release

2016

2012

2014

1984

2012

Current release

29.0.1, April 2024

7.4.1.1, 2021

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Open Source

Apache license v2

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

Linux
OS X
Unix

hosted

HP Open VMS

Linux
OS X
Windows

Data scheme

yes

schema-less columns are supported

schema-free

Flexible Schema (defined schema, partial schema, 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

yes

SQL

Support of SQL

yes

SQL for querying

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC

JDBC
RESTful HTTP/JSON API

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

RESTful HTTP API

Supported programming languages

C
Java
Perl
Python
R

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.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

Sharding

manual/auto, time-based

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

yes, via HDFS, S3 or other storage engines

yes

Implicit feature of the cloud service

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

yes, on a single node

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Access rights can be defined down to the item level

yes

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.