DBMS > AlaSQL vs. Apache Doris vs. EsgynDB vs. Greenplum vs. Yaacomo

System Properties Comparison AlaSQL vs. Apache Doris vs. EsgynDB vs. Greenplum vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

JavaScript DBMS library

An MPP-based analytics DBMS embracing the MySQL protocol

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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.

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Document store
Relational DBMS

Relational DBMS

Secondary database models

Document store
Spatial 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	0.57
Rank	#244	Overall
	#113	Relational DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	8.37
Rank	#48	Overall
	#30	Relational DBMS

Website

alasql.org

doris.apache.org
github.com/apache/doris

www.esgyn.cn

greenplum.org

yaacomo.com

Technical documentation

github.com/AlaSQL/alasql

github.com/apache/doris/wiki

docs.greenplum.org

Developer

Andrey Gershun & Mathias R. Wulff

Apache Software Foundation, originally contributed from Baidu

Esgyn

Pivotal Software Inc.

Q2WEB GmbH

Initial release

2014

2017

2015

2005

2009

Current release

1.2.2, February 2023

7.0.0, September 2023

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache Version 2.0

commercial

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

JavaScript

Java

C++, Java

Server operating systems

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

Linux

Android
Linux
Windows

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.

yes

since Version 4.2

Secondary indexes

yes

SQL

Support of SQL

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

yes

APIs and other access methods

JavaScript API

JDBC
MySQL client

ADO.NET
JDBC
ODBC

JDBC
ODBC

Supported programming languages

JavaScript

Java

All languages supporting JDBC/ODBC/ADO.Net

C
Java
Perl
Python
R

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication between multi datacenters

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

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

User concepts

Access control

fine grained access rights according to SQL-standard

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