DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Amazon Redshift vs. Bangdb vs. FoundationDB vs. Splice Machine

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Amazon Redshift vs. Bangdb vs. FoundationDB vs. Splice Machine

Editorial information provided by DB-Engines

Name

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.

Description

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

Large scale data warehouse service for use with business intelligence tools

Converged and high performance database for device data, events, time series, document and graph

Ordered key-value store. Core features are complimented by layers.

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Relational DBMS

Document store
Graph DBMS
Time Series DBMS

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Relational DBMS

Secondary database models

Spatial DBMS

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	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	1.03
Rank	#190	Overall
	#31	Document stores
	#28	Key-value stores
	#89	Relational DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

aws.amazon.com/redshift

bangdb.com

github.com/apple/foundationdb

splicemachine.com

Technical documentation

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

docs.aws.amazon.com/redshift

docs.bangdb.com

apple.github.io/foundationdb

splicemachine.com/how-it-works

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Amazon (based on PostgreSQL)

Sachin Sinha, BangDB

FoundationDB

Splice Machine

Initial release

2016

2012

2013

2014

Current release

BangDB 2.0, October 2021

6.2.28, November 2020

3.1, March 2021

License

Commercial or Open Source

commercial

Open Source

BSD 3

Open Source

Apache 2.0

Open Source

AGPL 3.0, commercial license 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

C, C++

C++

Java

Server operating systems

hosted

Linux

Linux
OS X
Windows

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

some layers support schemas

yes

Typing

predefined data types such as float or date

yes

yes: string, long, double, int, geospatial, stream, events

some layers support typing

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

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL like support with command line tool

supported in specific SQL layer only

yes

APIs and other access methods

JDBC
ODBC

Proprietary protocol
RESTful HTTP API

JDBC
Native Spark Datasource
ODBC

Supported programming languages

C
Java
Perl
Python
R

All languages supporting JDBC/ODBC

C
C#
C++
Java
Python

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

yes

user defined functions

in Python

in SQL-layer only

yes

Java

Triggers

yes

yes, Notifications (with Streaming only)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

selectable replication factor, Knob for CAP (enterprise version only)

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable consistency, set CAP knob accordingly

Linearizable consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

in SQL-layer only

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

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

yes

yes, run db with in-memory only mode

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes (enterprise version only)

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

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