DBMS > Alibaba Cloud Table Store vs. Amazon DocumentDB vs. Drizzle vs. LeanXcale

System Properties Comparison Alibaba Cloud Table Store vs. Amazon DocumentDB vs. Drizzle vs. LeanXcale

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

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

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Primary database model

Wide column store

Document store

Relational DBMS

Key-value store
Relational DBMS

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Website

www.alibabacloud.com/product/table-store

aws.amazon.com/documentdb

www.leanxcale.com

Technical documentation

www.alibabacloud.com/help/en/tablestore

aws.amazon.com/documentdb/resources

Developer

Alibaba

Drizzle project, originally started by Brian Aker

LeanXcale

Initial release

2016

2019

2008

2015

Current release

7.2.4, September 2012

License

Commercial or Open Source

commercial

Open Source

GNU GPL

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

C++

Server operating systems

hosted

FreeBSD
Linux
OS X

Data scheme

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

with proprietary extensions

yes

through Apache Derby

APIs and other access methods

HTTP API

proprietary protocol using JSON (MongoDB compatible)

JDBC

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Supported programming languages

Java
Python

Go
Java
JavaScript (Node.js)
PHP
Python

C
C++
Java
PHP

C
Java
Scala

Server-side scripts

Stored procedures

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

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)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

Atomic single-row operations

Atomic single-document operations

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.

yes

User concepts

Access control

Access rights based on subaccounts and tokens

Access rights for users and roles

Pluggable authentication mechanisms

e.g. LDAP, HTTP

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