DBMS > EXASOL vs. HyperSQL vs. OrientDB vs. PouchDB vs. Snowflake

System Properties Comparison EXASOL vs. HyperSQL vs. OrientDB vs. PouchDB vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Multi-model DBMS (Document, Graph, Key/Value)

JavaScript DBMS with an API inspired by CouchDB

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store

Document store

Relational DBMS

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

Score	1.76
Rank	#139	Overall
	#62	Relational DBMS

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	3.25
Rank	#89	Overall
	#16	Document stores
	#6	Graph DBMS
	#13	Key-value stores

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

Technical documentation

www.exasol.com/resources

hsqldb.org/web/hsqlDocsFrame.html

www.orientdb.com/docs/last/index.html

pouchdb.com/guides

docs.snowflake.net/manuals/index.html

Developer

Exasol

OrientDB LTD; CallidusCloud; SAP

Apache Software Foundation

Snowflake Computing Inc.

Initial release

2000

2001

2010

2012

2014

Current release

2.7.2, June 2023

3.2.29, March 2024

7.1.1, June 2019

License

Commercial or Open Source

commercial

Open Source

based on BSD license

Open Source

Apache version 2

Open Source

commercial

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

Java

JavaScript

Server operating systems

All OS with a Java VM

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

All OS with a Java JDK (>= JDK 6)

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

hosted

Data scheme

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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.

yes

Secondary indexes

yes

via views

SQL

Support of SQL

yes

SQL-like query language, no joins

yes

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

HTTP API

JDBC via HTTP
JDBC
ODBC

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

HTTP REST

only for PouchDB Server
JavaScript API

CLI Client
JDBC
ODBC

Supported programming languages

Java
Lua
Python
R

All languages supporting JDBC/ODBC
Java

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

JavaScript

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

Java, SQL

Java, Javascript

View functions in JavaScript

user defined functions

Triggers

yes

Hooks

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

with a proxy-based framework, named couchdb-lounge

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

could be achieved with distributed queries

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

Access rights for users and roles; record level security configurable

Users with fine-grained authorization concept, user roles and pluggable authentication

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