DBMS > EXASOL vs. Greenplum vs. LokiJS vs. Snowflake

System Properties Comparison EXASOL vs. Greenplum vs. LokiJS vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

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

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

In-memory JavaScript DBMS

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

Primary database model

Relational DBMS

Document store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	8.37
Rank	#48	Overall
	#30	Relational DBMS

Score	0.43
Rank	#264	Overall
	#42	Document stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.exasol.com

greenplum.org

github.com/techfort/LokiJS

www.snowflake.com

Technical documentation

www.exasol.com/resources

docs.greenplum.org

techfort.github.io/LokiJS

docs.snowflake.net/manuals/index.html

Developer

Exasol

Pivotal Software Inc.

Snowflake Computing Inc.

Initial release

2000

2005

2014

Current release

7.0.0, September 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

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

JavaScript

Server operating systems

Linux

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

hosted

Data scheme

yes

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

since Version 4.2

yes

Secondary indexes

yes

via views

SQL

Support of SQL

yes

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

JDBC
ODBC

JavaScript API

CLI Client
JDBC
ODBC

Supported programming languages

Java
Lua
Python
R

C
Java
Perl
Python
R

JavaScript

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

yes

View functions in JavaScript

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

atomic operations within a single collection possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

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

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

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