DBMS > Alibaba Cloud PolarDB vs. Amazon Redshift vs. etcd vs. IBM Db2 Event Store

System Properties Comparison Alibaba Cloud PolarDB vs. Amazon Redshift vs. etcd vs. IBM Db2 Event Store

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Editorial information provided by DB-Engines

Name

Description

A cloud-native relational database compatible with MySQL, PostgreSQL, and Oracle. Designed for business critical applications.

Large scale data warehouse service for use with business intelligence tools

A distributed reliable key-value store

Distributed Event Store optimized for Internet of Things use cases

Primary database model

Relational DBMS

Key-value store

Event Store
Time Series DBMS

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

Score	0.66
Rank	#235	Overall
	#108	Relational DBMS

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	7.03
Rank	#54	Overall
	#5	Key-value stores

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Website

www.alibabacloud.com/product/polardb

aws.amazon.com/redshift

etcd.io
github.com/etcd-io/etcd

www.ibm.com/products/db2-event-store

Technical documentation

www.alibabacloud.com/help/en/polardb/product-overview

docs.aws.amazon.com/redshift

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

www.ibm.com/docs/en/db2-event-store

Developer

Alibaba

Amazon (based on PostgreSQL)

IBM

Initial release

2012

2017

Current release

3.4, August 2019

2.0

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

free developer edition 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 and C++

Server operating systems

hosted

FreeBSD
Linux
Windows

experimental

Linux

Linux, macOS, Windows for the developer addition

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

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

through the embedded Spark runtime

APIs and other access methods

JDBC
ODBC

gRPC
JSON over HTTP

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

Supported programming languages

Java
Python

All languages supporting JDBC/ODBC

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

Server-side scripts

Stored procedures

yes

user defined functions

in Python

yes

Triggers

yes

yes, watching key changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

Active-active shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

More information provided by the system vendor

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Typical application scenarios

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Licensing and pricing models

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