DBMS > Alibaba Cloud Table Store vs. Datomic vs. Lovefield vs. Sequoiadb

System Properties Comparison Alibaba Cloud Table Store vs. Datomic vs. Lovefield vs. Sequoiadb

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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

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Embeddable relational database for web apps written in pure JavaScript

NewSQL database with distributed OLTP and SQL

Primary database model

Wide column store

Relational DBMS

Document 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	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Website

www.alibabacloud.com/product/table-store

www.datomic.com

google.github.io/lovefield

www.sequoiadb.com

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.datomic.com

github.com/google/lovefield/blob/master/docs/spec_index.md

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Alibaba

Cognitect

Google

Sequoiadb Ltd.

Initial release

2016

2012

2014

2013

Current release

1.0.6735, June 2023

2.1.12, February 2017

License

Commercial or Open Source

commercial

limited edition free

Open Source

Apache 2.0

Open Source

Server: AGPL; Client: Apache V2

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Clojure

JavaScript

C++

Server operating systems

hosted

All OS with a Java VM

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

via JavaScript builder pattern

SQL-like query language

APIs and other access methods

HTTP API

RESTful HTTP API

proprietary protocol using JSON

Supported programming languages

Java
Python

Clojure
Java

JavaScript

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

yes

Transaction Functions

JavaScript

Triggers

By using transaction functions

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

But extensive use of caching in the application peers

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

But extensive use of caching in the application peers

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

recommended only for testing and development

yes

using MemoryDB

User concepts

Access control

Access rights based on subaccounts and tokens

simple password-based access control

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