DBMS > Alibaba Cloud Table Store vs. Amazon DynamoDB vs. CockroachDB vs. Hazelcast vs. PlanetScale

System Properties Comparison Alibaba Cloud Table Store vs. Amazon DynamoDB vs. CockroachDB vs. Hazelcast vs. PlanetScale

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

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

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.

A widely adopted in-memory data grid

Scalable, distributed, serverless MySQL database platform built on top of Vitess

Primary database model

Wide column store

Document store
Key-value store

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

Document store
Spatial DBMS

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	1.59
Rank	#151	Overall
	#70	Relational DBMS

Website

www.alibabacloud.com/product/table-store

aws.amazon.com/dynamodb

www.cockroachlabs.com

hazelcast.com

planetscale.com

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.aws.amazon.com/dynamodb

www.cockroachlabs.com/docs

hazelcast.org/imdg/docs

planetscale.com/docs

Developer

Alibaba

Amazon

Cockroach Labs

Hazelcast

PlanetScale

Initial release

2016

2012

2015

2008

2020

Current release

24.1.0, May 2024

5.3.6, November 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache 2.0, commercial license available

Open Source

Apache Version 2; commercial licenses available

commercial

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

Server operating systems

hosted

Linux
macOS
Windows

All OS with a Java VM

Docker
Linux
macOS

Data scheme

schema-free

dynamic schema

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

the object must implement a serialization strategy

Secondary indexes

yes

SQL

Support of SQL

yes, wire compatible with PostgreSQL

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

HTTP API

RESTful HTTP API

JDBC

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

Java
Python

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

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

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

yes

proprietary syntax

Triggers

yes

by integration with AWS Lambda

yes

Events

yes

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

yes

Replicated Map

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

Atomic single-row operations

ACID

ACID across one or more tables within a single AWS account and region

ACID

one or two-phase-commit; repeatable reads; read commited

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

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

Access rights based on subaccounts and tokens

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

Role-based access control

Users with fine-grained authorization concept

no user groups or roles

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