DBMS > Google BigQuery vs. OpenEdge vs. TigerGraph

System Properties Comparison Google BigQuery vs. OpenEdge vs. TigerGraph

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Application development environment with integrated database management system

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

Primary database model

Relational DBMS

Graph DBMS

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Trend Chart

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	3.51
Rank	#86	Overall
	#46	Relational DBMS

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Website

cloud.google.com/bigquery

www.progress.com/openedge

www.tigergraph.com

Technical documentation

cloud.google.com/bigquery/docs

documentation.progress.com/output/ua/OpenEdge_latest

docs.tigergraph.com

Developer

Google

Progress Software Corporation

Initial release

2010

1984

2017

Current release

OpenEdge 12.2, March 2020

License

Commercial or Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Server operating systems

hosted

AIX
HP-UX
Linux
Solaris
Windows

Linux

Data scheme

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

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

SQL-like query language (GSQL)

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC

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

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Progress proprietary ABL (Advanced Business Language)

C++
Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

since Version 11.4

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

User concepts

Access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Users and groups

Role-based access control

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