DBMS > Alibaba Cloud Table Store vs. Amazon DynamoDB vs. Google Cloud Datastore vs. Memcached vs. ObjectBox

System Properties Comparison Alibaba Cloud Table Store vs. Amazon DynamoDB vs. Google Cloud Datastore vs. Memcached vs. ObjectBox

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

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

In-memory key-value store, originally intended for caching

Extremely fast embedded database for small devices, IoT and Mobile

Primary database model

Wide column store

Document store
Key-value store

Document store

Key-value store

Object oriented DBMS

Secondary database models

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

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	19.42
Rank	#32	Overall
	#4	Key-value stores

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Website

www.alibabacloud.com/product/table-store

aws.amazon.com/dynamodb

cloud.google.com/datastore

www.memcached.org

objectbox.io

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.aws.amazon.com/dynamodb

cloud.google.com/datastore/docs

github.com/memcached/memcached/wiki

docs.objectbox.io

Developer

Alibaba

Amazon

Google

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

ObjectBox Limited

Initial release

2016

2012

2008

2003

2017

Current release

1.6.25, March 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

BSD license

Open Source

Apache License 2.0

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 and C++

Server operating systems

hosted

FreeBSD
Linux
OS X
Unix
Windows

Android
iOS
Linux
macOS
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, details here

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

SQL-like query language (GQL)

APIs and other access methods

HTTP API

RESTful HTTP API

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

Proprietary protocol

Proprietary native API

Supported programming languages

Java
Python

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

Server-side scripts

Stored procedures

using Google App Engine

Triggers

yes

by integration with AWS Lambda

Callbacks using the Google Apps Engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Multi-source replication using Paxos

none

Repcached, a Memcached patch, provides this functionallity

online/offline synchronization between client and server

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

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

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

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.

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)

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

yes

using SASL (Simple Authentication and Security Layer) protocol

yes

More information provided by the system vendor

News

Edge AI: The era of on-device AI
23 April 2024

In-Memory Database Use Cases
15 February 2024

Data Viewer for Objects – announcing ObjectBox Admin
14 November 2023

Vector Databases for Edge AI
9 August 2023

Vector Database Release for Flutter / Dart + Python
13 June 2023

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