DBMS > AlaSQL vs. Elasticsearch vs. HyperSQL vs. Microsoft Azure Cosmos DB vs. SwayDB

System Properties Comparison AlaSQL vs. Elasticsearch vs. HyperSQL vs. Microsoft Azure Cosmos DB vs. SwayDB

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Globally distributed, horizontally scalable, multi-model database service

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Document store
Relational DBMS

Search engine

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Key-value store

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Spatial DBMS

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

Score	0.51
Rank	#256	Overall
	#40	Document stores
	#118	Relational DBMS

Score	132.83
Rank	#7	Overall
	#1	Search engines

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Website

alasql.org

www.elastic.co/elasticsearch

hsqldb.org

azure.microsoft.com/services/cosmos-db

swaydb.simer.au

Technical documentation

github.com/AlaSQL/alasql

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

hsqldb.org/web/hsqlDocsFrame.html

learn.microsoft.com/azure/cosmos-db

Developer

Andrey Gershun & Mathias R. Wulff

Elastic

Microsoft

Simer Plaha

Initial release

2014

2010

2001

2014

2018

Current release

8.6, January 2023

2.7.2, June 2023

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Elastic License

Open Source

based on BSD license

commercial

Open Source

GNU Affero GPL V3.0

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

JavaScript

Java

Scala

Server operating systems

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

All OS with a Java VM

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

hosted

Data scheme

schema-free

Flexible type definitions. Once a type is defined, it is persistent

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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

All search fields are automatically indexed

yes

All properties auto-indexed by default

SQL

Support of SQL

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

SQL-like query language

yes

SQL-like query language

APIs and other access methods

JavaScript API

Java API
RESTful HTTP/JSON API

HTTP API

JDBC via HTTP
JDBC
ODBC

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Supported programming languages

JavaScript

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

All languages supporting JDBC/ODBC
Java

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

Java, SQL

JavaScript

Triggers

yes

by using the 'percolation' feature

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

none

yes

Implicit feature of the cloud service

none

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

Multi-item ACID transactions with snapshot isolation within a partition

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

In-memory capabilities

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

yes

Memcached and Redis integration

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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