DBMS > AgensGraph vs. Alibaba Cloud AnalyticDB for PostgreSQL vs. Google Cloud Spanner vs. Snowflake vs. WakandaDB

System Properties Comparison AgensGraph vs. Alibaba Cloud AnalyticDB for PostgreSQL vs. Google Cloud Spanner vs. Snowflake vs. WakandaDB

Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

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

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.

Cloud-based data warehousing service for structured and semi-structured data

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

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS

Object oriented DBMS

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

Score	0.17
Rank	#320	Overall
	#29	Graph DBMS
	#143	Relational DBMS

Score	0.79
Rank	#213	Overall
	#101	Relational DBMS

Score	2.69
Rank	#101	Overall
	#51	Relational DBMS

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

bitnine.net/agensgraph

www.alibabacloud.com/product/hybriddb-postgresql

cloud.google.com/spanner

www.snowflake.com

wakanda.github.io

Technical documentation

bitnine.net/documentation

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

cloud.google.com/spanner/docs

docs.snowflake.net/manuals/index.html

wakanda.github.io/doc

Developer

Bitnine Global Inc.

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Google

Snowflake Computing Inc.

Wakanda SAS

Initial release

2016

2017

2014

2012

Current release

2.1, December 2018

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Apache License 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

C++, JavaScript

Server operating systems

Linux
OS X
Windows

hosted

Linux
OS X
Windows

Data scheme

depending on used data model

yes

support of semi-structured data formats (JSON, XML, Avro)

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

Cypher Query Language
JDBC

JDBC
ODBC

gRPC (using protocol buffers) API
JDBC

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

CLI Client
JDBC
ODBC

RESTful HTTP API

Supported programming languages

C
Java
JavaScript
Python

C
Java
Perl
Python
R

Go
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

JavaScript

Server-side scripts

Stored procedures

yes

user defined functions

yes

Triggers

yes

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

Implicit feature of the cloud service

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

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

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of 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 rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Users with fine-grained authorization concept, user roles and pluggable authentication

yes

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