DBMS > Alibaba Cloud Table Store vs. Amazon DynamoDB vs. BaseX vs. Google Cloud Bigtable vs. Graphite

System Properties Comparison Alibaba Cloud Table Store vs. Amazon DynamoDB vs. BaseX vs. Google Cloud Bigtable vs. Graphite

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

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Primary database model

Wide column store

Document store
Key-value store

Native XML DBMS

Key-value store
Wide column store

Time Series 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	1.84
Rank	#135	Overall
	#4	Native XML DBMS

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	4.83
Rank	#67	Overall
	#4	Time Series DBMS

Website

www.alibabacloud.com/product/table-store

aws.amazon.com/dynamodb

basex.org

cloud.google.com/bigtable

github.com/graphite-project/graphite-web

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.aws.amazon.com/dynamodb

docs.basex.org

cloud.google.com/bigtable/docs

graphite.readthedocs.io

Developer

Alibaba

Amazon

BaseX GmbH

Google

Chris Davis

Initial release

2016

2012

2007

2015

2006

Current release

11.0, June 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

BSD license

commercial

Open Source

Apache 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

Java

Python

Server operating systems

hosted

Linux
OS X
Windows

hosted

Linux
Unix

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

XQuery supports types

Numeric data only

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

APIs and other access methods

HTTP API

RESTful HTTP API

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

HTTP API
Sockets

Supported programming languages

Java
Python

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

by integration with AWS Lambda

yes

via events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

none

Internal replication in Colossus, and regional replication between two clusters in different zones

none

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 (for a single cluster), Eventual consistency (for two or more replicated clusters)

none

Foreign keys

Referential integrity

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

multiple readers, single writer

Atomic single-row operations

Concurrency

Support for concurrent manipulation of data

yes

locking

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)

Users with fine-grained authorization concept on 4 levels

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

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