DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Amazon Redshift vs. HarperDB vs. Spark SQL vs. Stardog

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Amazon Redshift vs. HarperDB vs. Spark SQL vs. Stardog

Editorial information provided by DB-Engines

Name

Description

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

Large scale data warehouse service for use with business intelligence tools

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

Spark SQL is a component on top of 'Spark Core' for structured data processing

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

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

Score	0.68
Rank	#231	Overall
	#105	Relational DBMS

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

www.alibabacloud.com/product/hybriddb-postgresql

aws.amazon.com/redshift

www.harperdb.io

spark.apache.org/sql

www.stardog.com

Technical documentation

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

docs.aws.amazon.com/redshift

docs.harperdb.io/docs

spark.apache.org/docs/latest/sql-programming-guide.html

docs.stardog.com

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Amazon (based on PostgreSQL)

HarperDB

Apache Software Foundation

Stardog-Union

Initial release

2016

2012

2017

2014

2010

Current release

3.1, August 2021

3.5.0 ( 2.13), September 2023

7.3.0, May 2020

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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

Node.js

Scala

Java

Server operating systems

hosted

Linux
OS X

Linux
OS X
Windows

Linux
macOS
Windows

Data scheme

yes

dynamic schema

yes

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

yes

JSON data 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

Import/export of XML data possible

Secondary indexes

yes

restricted

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like data manipulation statements

SQL-like DML and DDL statements

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

JDBC
ODBC

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

C
Java
Perl
Python
R

All languages supporting JDBC/ODBC

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

Java
Python
R
Scala

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions

in Python

Custom Functions

since release 3.1

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

A table resides as a whole on one (or more) nodes in a cluster

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

the nodes on which a table resides can be defined

none

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

relationships in graphs

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

yes

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

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.