DBMS > Apache Drill vs. EDB Postgres vs. JaguarDB

System Properties Comparison Apache Drill vs. EDB Postgres vs. JaguarDB

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Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.

Performant, highly scalable DBMS for AI and IoT applications

Primary database model

Document store
Relational DBMS

Relational DBMS

Key-value store
Vector DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	2.02
Rank	#124	Overall
	#22	Document stores
	#59	Relational DBMS

Score	1.91
Rank	#130	Overall
	#60	Relational DBMS

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#15	Vector DBMS

Website

drill.apache.org

www.enterprisedb.com

www.jaguardb.com

Technical documentation

drill.apache.org/docs

www.enterprisedb.com/docs

www.jaguardb.com/support.html

Developer

Apache Software Foundation

EnterpriseDB

DataJaguar, Inc.

Initial release

2012

2005

2015

Current release

1.20.3, January 2023

14, December 2021

3.3 July 2023

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

BSD for PostgreSQL-components

Open Source

GPL V3.0

Cloud-based only

Only available as a cloud service

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Implementation language

C++

the server part. Clients available in other languages

Server operating systems

Linux
OS X
Windows

Linux
Windows

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

standard with numerous extensions

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
ODBC

Supported programming languages

C++

.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

by hash, list or range

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source 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

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

In-memory capabilities

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

Depending on the underlying data source

User concepts

Access control

Depending on the underlying data source

fine grained access rights according to SQL-standard

rights management via user accounts

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More resources

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