DBMS > EJDB vs. Hive vs. IBM Db2 vs. OpenEdge vs. SQLite

System Properties Comparison EJDB vs. Hive vs. IBM Db2 vs. OpenEdge vs. SQLite

Editorial information provided by DB-Engines

Name

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Common in IBM host environments, 2 different versions for host and Windows/Linux

Application development environment with integrated database management system

Widely used embeddable, in-process RDBMS

Primary database model

Document store

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Relational DBMS

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	128.46
Rank	#8	Overall
	#5	Relational DBMS

Score	3.51
Rank	#86	Overall
	#46	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

github.com/Softmotions/ejdb

hive.apache.org

www.ibm.com/products/db2

www.progress.com/openedge

www.sqlite.org

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

cwiki.apache.org/confluence/display/Hive/Home

www.ibm.com/docs/en/db2

documentation.progress.com/output/ua/OpenEdge_latest

www.sqlite.org/docs.html

Developer

Softmotions

Apache Software Foundation

initially developed by Facebook

IBM

Progress Software Corporation

Dwayne Richard Hipp

Initial release

2012

1983

host version

1984

2000

Current release

3.1.3, April 2022

12.1, October 2016

OpenEdge 12.2, March 2020

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

GPLv2

Open Source

Apache Version 2

commercial

free version is available

commercial

Open Source

Public Domain

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

Java

C and C++

Server operating systems

server-less

All OS with a Java VM

AIX
HP-UX
Linux
Solaris
Windows
z/OS

AIX
HP-UX
Linux
Solaris
Windows

server-less

Data scheme

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

not rigid because of 'dynamic typing' concept.

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-like DML and DDL statements

yes

close to SQL 92

yes

SQL-92 is not fully supported

APIs and other access methods

in-process shared library

JDBC
ODBC
Thrift

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

C++
Java
PHP
Python

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

Progress proprietary ABL (Advanced Business Language)

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

only with Windows/Unix/Linux Version

horizontal partitioning

since Version 11.4

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

yes

with separate tools (MQ, InfoSphere)

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

via file-system locks

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.

yes

User concepts

Access control

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

Users and groups

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