DBMS > Alibaba Cloud Table Store vs. Drizzle vs. LeanXcale vs. Realm

System Properties Comparison Alibaba Cloud Table Store vs. Drizzle vs. LeanXcale vs. Realm

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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

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

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Primary database model

Wide column store

Relational DBMS

Key-value store
Relational DBMS

Document store

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

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

Score	7.60
Rank	#52	Overall
	#9	Document stores

Website

www.alibabacloud.com/product/table-store

www.leanxcale.com

realm.io

Technical documentation

www.alibabacloud.com/help/en/tablestore

realm.io/docs

Developer

Alibaba

Drizzle project, originally started by Brian Aker

LeanXcale

Realm, acquired by MongoDB in May 2019

Initial release

2016

2008

2015

2014

Current release

7.2.4, September 2012

License

Commercial or Open Source

commercial

Open Source

GNU GPL

commercial

Open Source

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

Android
Backend: server-less
iOS
Windows

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

JDBC

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Supported programming languages

Java
Python

C
C++
Java
PHP

C
Java
Scala

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

runs within the applications so server-side scripts are unnecessary

Triggers

hooks for callbacks inside the server can be used.

yes

Change Listeners

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

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row 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

In-Memory realm

User concepts

Access control

Access rights based on subaccounts and tokens

Pluggable authentication mechanisms

e.g. LDAP, HTTP

yes

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