DBMS > Apache Druid vs. Google BigQuery vs. OpenEdge

System Properties Comparison Apache Druid vs. Google BigQuery vs. OpenEdge

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Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Large scale data warehouse service with append-only tables

Application development environment with integrated database management system

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

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Trend Chart

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	3.51
Rank	#86	Overall
	#46	Relational DBMS

Website

druid.apache.org

cloud.google.com/bigquery

www.progress.com/openedge

Technical documentation

druid.apache.org/docs/latest/design

cloud.google.com/bigquery/docs

documentation.progress.com/output/ua/OpenEdge_latest

Developer

Apache Software Foundation and contributors

Google

Progress Software Corporation

Initial release

2012

2010

1984

Current release

29.0.1, April 2024

OpenEdge 12.2, March 2020

License

Commercial or Open Source

Open Source

Apache license v2

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

Java

Server operating systems

Linux
OS X
Unix

hosted

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-less columns are supported

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

SQL for querying

yes

close to SQL 92

APIs and other access methods

JDBC
RESTful HTTP/JSON API

RESTful HTTP/JSON API

JDBC
ODBC

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Progress proprietary ABL (Advanced Business Language)

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

horizontal partitioning

since Version 11.4

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

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

Google Cloud Identity & Access Management (IAM)

Users and groups

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