DBMS > Alibaba Cloud Table Store vs. Amazon Redshift vs. CockroachDB vs. IBM Db2 Event Store

System Properties Comparison Alibaba Cloud Table Store vs. Amazon Redshift vs. CockroachDB vs. IBM Db2 Event Store

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Editorial information provided by DB-Engines

Name

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

Large scale data warehouse service for use with business intelligence tools

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

Distributed Event Store optimized for Internet of Things use cases

Primary database model

Wide column store

Relational DBMS

Event Store
Time Series DBMS

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Website

www.alibabacloud.com/product/table-store

aws.amazon.com/redshift

www.cockroachlabs.com

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

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.aws.amazon.com/redshift

www.cockroachlabs.com/docs

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

Developer

Alibaba

Amazon (based on PostgreSQL)

Cockroach Labs

IBM

Initial release

2016

2012

2015

2017

Current release

23.1.1, May 2023

2.0

License

Commercial or Open Source

commercial

Open Source

Apache 2.0, commercial license available

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

Linux
macOS
Windows

Linux

Linux, macOS, Windows for the developer addition

Data scheme

schema-free

yes

dynamic schema

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes, wire compatible with PostgreSQL

yes

through the embedded Spark runtime

APIs and other access methods

HTTP API

JDBC
ODBC

JDBC

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

Supported programming languages

Java
Python

All languages supporting JDBC/ODBC

C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust

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

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Multi-source replication using RAFT

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

yes

Transaction concepts

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

Atomic single-row operations

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

Access rights based on subaccounts and tokens

fine grained access rights according to SQL-standard

Role-based access control

fine grained access rights according to SQL-standard

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