DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. EventStoreDB vs. Google BigQuery vs. Riak KV vs. Sadas Engine

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. EventStoreDB vs. Google BigQuery vs. Riak KV vs. Sadas Engine

Editorial information provided by DB-Engines

Name

Description

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

Industrial-strength, open-source database solution built from the ground up for event sourcing.

Large scale data warehouse service with append-only tables

Distributed, fault tolerant key-value store

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

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

Score	0.62
Rank	#241	Overall
	#110	Relational DBMS

Score	1.14
Rank	#181	Overall
	#1	Event Stores

Score	61.90
Rank	#19	Overall
	#13	Relational DBMS

Score	4.44
Rank	#80	Overall
	#9	Key-value stores

Score	0.03
Rank	#379	Overall
	#156	Relational DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

www.eventstore.com

cloud.google.com/bigquery

www.sadasengine.com

Technical documentation

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

developers.eventstore.com

cloud.google.com/bigquery/docs

www.tiot.jp/riak-docs/riak/kv/latest

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Event Store Limited

Google

OpenSource, formerly Basho Technologies

SADAS s.r.l.

Initial release

2016

2012

2010

2009

2006

Current release

21.2, February 2021

3.2.0, December 2022

8.0

License

Commercial or Open Source

commercial

Open Source

commercial

Open Source

Apache version 2, commercial enterprise edition

commercial

free trial version available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Erlang

C++

Server operating systems

hosted

Linux
Windows

hosted

Linux
OS X

AIX
Linux
Windows

Data scheme

yes

schema-free

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

restricted

yes

SQL

Support of SQL

yes

APIs and other access methods

JDBC
ODBC

RESTful HTTP/JSON API

HTTP API
Native Erlang Interface

JDBC
ODBC
Proprietary protocol

Supported programming languages

C
Java
Perl
Python
R

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Sharding

no "single point of failure"

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

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.

yes

managed by 'Learn by Usage'

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)

yes, using Riak Security

Access rights for users, groups and roles according to SQL-standard

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