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

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

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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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Wide column store

Relational DBMS

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

Score	0.25
Rank	#294	Overall
	#12	Wide column stores

Score	1.55
Rank	#144	Overall
	#67	Relational DBMS

Score	3.14
Rank	#85	Overall
	#46	Relational DBMS

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Website

www.alibabacloud.com/product/table-store

www.datomic.com

hsqldb.org

google.github.io/lovefield

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.datomic.com

hsqldb.org/web/hsqlDocsFrame.html

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

Developer

Alibaba

Cognitect

Google

Initial release

2016

2012

2001

2014

Current release

1.0.7180, July 2024

2.7.2, June 2023

2.1.12, February 2017

License

Commercial or Open Source

commercial

limited edition free

Open Source

based on BSD license

Open Source

Apache 2.0

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

Java

JavaScript

Server operating systems

hosted

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

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

tested with Chrome, Firefox, IE, Safari

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

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

HTTP API

RESTful HTTP API

HTTP API

JDBC via HTTP
JDBC
ODBC

Supported programming languages

Java
Python

Clojure
Java

All languages supporting JDBC/ODBC
Java

JavaScript

Server-side scripts

Stored procedures

yes

Transaction Functions

Java, SQL

Triggers

By using transaction functions

yes

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

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

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

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

yes

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

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

fine grained access rights according to SQL-standard

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