DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Amazon Neptune vs. Apache Kylin vs. Kinetica vs. VoltDB

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Amazon Neptune vs. Apache Kylin vs. Kinetica vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

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

Fast, reliable graph database built for the cloud

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

Fully vectorized database across both GPUs and CPUs

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational DBMS

Graph DBMS
RDF store

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	0.68
Rank	#231	Overall
	#105	Relational DBMS

Score	2.20
Rank	#119	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	1.18
Rank	#172	Overall
	#79	Relational DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

aws.amazon.com/neptune

kylin.apache.org

www.kinetica.com

www.voltdb.com

Technical documentation

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

aws.amazon.com/neptune/developer-resources

kylin.apache.org/docs

docs.kinetica.com

docs.voltdb.com

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Amazon

Apache Software Foundation, originally contributed from eBay Inc

Kinetica

VoltDB Inc.

Initial release

2016

2017

2015

2012

2010

Current release

3.1.0, July 2020

7.1, August 2021

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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, C++

Java, C++

Server operating systems

hosted

Linux

Linux
OS X

for development

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

SQL

Support of SQL

yes

ANSI SQL for queries (using Apache Calcite)

SQL-like DML and DDL statements

yes

only a subset of SQL 99

APIs and other access methods

JDBC
ODBC

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

JDBC
ODBC
RESTful HTTP API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C
Java
Perl
Python
R

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

C++
Java
JavaScript (Node.js)
Python

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions

Java

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

with encyption-at-rest

yes

Snapshots and command logging

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

GPU vRAM or System RAM

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Access rights for users and roles on table level

Users and roles with access to stored procedures

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