DBMS > Alibaba Cloud Table Store vs. Amazon DynamoDB vs. EsgynDB vs. Geode vs. JaguarDB

System Properties Comparison Alibaba Cloud Table Store vs. Amazon DynamoDB vs. EsgynDB vs. Geode vs. JaguarDB

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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

Performant, highly scalable DBMS for AI and IoT applications

Primary database model

Wide column store

Document store
Key-value store

Relational DBMS

Key-value store

Key-value store
Vector DBMS

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

Score	0.31
Rank	#297	Overall
	#11	Wide column stores

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	1.86
Rank	#134	Overall
	#24	Key-value stores

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#13	Vector DBMS

Website

www.alibabacloud.com/product/table-store

aws.amazon.com/dynamodb

www.esgyn.cn

geode.apache.org

www.jaguardb.com

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.aws.amazon.com/dynamodb

geode.apache.org/docs

www.jaguardb.com/support.html

Developer

Alibaba

Amazon

Esgyn

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

DataJaguar, Inc.

Initial release

2016

2012

2015

2002

2015

Current release

1.1, February 2017

3.3 July 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

GPL V3.0

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++, Java

Java

C++

the server part. Clients available in other languages

Server operating systems

hosted

Linux

All OS with a Java VM

the JDK (8 or later) is also required

Linux

Data scheme

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language (OQL)

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

APIs and other access methods

HTTP API

RESTful HTTP API

ADO.NET
JDBC
ODBC

Java Client API
Memcached protocol
RESTful HTTP API

JDBC
ODBC

Supported programming languages

Java
Python

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

.Net
All JVM based languages
C++
Groovy
Java
Scala

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

Triggers

yes

by integration with AWS Lambda

yes

Cache Event Listeners

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

Multi-source replication between multi datacenters

Multi-source 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

Eventual Consistency

Foreign keys

Referential integrity

yes

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

yes, on a single node

Concurrency

Support for concurrent manipulation of data

yes

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)

fine grained access rights according to SQL-standard

Access rights per client and object definable

rights management via user accounts

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