DBMS > AlaSQL vs. Graph Engine vs. Greenplum vs. TigerGraph

System Properties Comparison AlaSQL vs. Graph Engine vs. Greenplum vs. TigerGraph

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

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.

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Document store
Relational DBMS

Graph DBMS
Key-value store

Relational DBMS

Graph DBMS

Secondary database models

Document store
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	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

Technical documentation

github.com/AlaSQL/alasql

www.graphengine.io/docs/manual

docs.greenplum.org

docs.tigergraph.com

Developer

Andrey Gershun & Mathias R. Wulff

Microsoft

Pivotal Software Inc.

Initial release

2014

2010

2005

2017

Current release

7.0.0, September 2023

License

Commercial or Open Source

Open Source

MIT-License

Open Source

MIT License

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

.NET and C

C++

Server operating systems

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

.NET

Linux

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

SQL-like query language (GSQL)

APIs and other access methods

JavaScript API

RESTful HTTP API

JDBC
ODBC

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

JavaScript

C#
C++
F#
Visual Basic

C
Java
Perl
Python
R

C++
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

Relationships in graphs

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

Role-based access control

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