DBMS > AlaSQL vs. Datomic vs. HugeGraph

System Properties Comparison AlaSQL vs. Datomic vs. HugeGraph

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

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

A fast-speed and highly-scalable Graph DBMS

Primary database model

Document store
Relational DBMS

Relational DBMS

Graph DBMS

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

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Website

alasql.org

www.datomic.com

github.com/hugegraph
hugegraph.apache.org

Technical documentation

github.com/AlaSQL/alasql

docs.datomic.com

hugegraph.apache.org/docs

Developer

Andrey Gershun & Mathias R. Wulff

Cognitect

Baidu

Initial release

2014

2012

2018

Current release

1.0.6735, June 2023

0.9

License

Commercial or Open Source

Open Source

MIT-License

commercial

limited edition free

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

JavaScript

Java, Clojure

Java

Server operating systems

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

All OS with a Java VM

Linux
macOS
Unix

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

also supports composite index and range index

SQL

Support of SQL

Close to SQL99, but no user access control, stored procedures and host language bindings.

APIs and other access methods

JavaScript API

RESTful HTTP API

Java API
RESTful HTTP API
TinkerPop Gremlin

Supported programming languages

JavaScript

Clojure
Java

Groovy
Java
Python

Server-side scripts

Stored procedures

yes

Transaction Functions

asynchronous Gremlin script jobs

Triggers

yes

By using transaction functions

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

yes

depending on used storage backend, e.g. Cassandra and HBase

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes

depending on used storage backend, e.g. Cassandra and HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

edges in graph

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

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

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

User concepts

Access control

Users, roles and permissions

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