DBMS > BigchainDB vs. IBM Db2 vs. OpenEdge vs. SQLite vs. Vitess

System Properties Comparison BigchainDB vs. IBM Db2 vs. OpenEdge vs. SQLite vs. Vitess

Editorial information provided by DB-Engines

Name

Description

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

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

Scalable, distributed, cloud-native DBMS, extending MySQL

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

Document store
Spatial DBMS

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

Score	0.79
Rank	#212	Overall
	#36	Document stores

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

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Website

www.bigchaindb.com

www.ibm.com/products/db2

www.progress.com/openedge

www.sqlite.org

vitess.io

Technical documentation

bigchaindb.readthedocs.io/en/latest

www.ibm.com/docs/en/db2

documentation.progress.com/output/ua/OpenEdge_latest

www.sqlite.org/docs.html

vitess.io/docs

Developer

IBM

Progress Software Corporation

Dwayne Richard Hipp

The Linux Foundation, PlanetScale

Initial release

2016

1983

host version

1984

2000

2013

Current release

12.1, October 2016

OpenEdge 12.2, March 2020

3.45.3 (15 April 2024), April 2024

15.0.2, December 2022

License

Commercial or Open Source

Open Source

AGPL v3

commercial

free version is available

commercial

Open Source

Public Domain

Open Source

Apache Version 2.0, commercial licenses available

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

Python

C and C++

Server operating systems

Linux

AIX
HP-UX
Linux
Solaris
Windows
z/OS

AIX
HP-UX
Linux
Solaris
Windows

server-less

Docker
Linux
macOS

Data scheme

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

yes

SQL-92 is not fully supported

yes

with proprietary extensions

APIs and other access methods

CLI Client
RESTful HTTP API

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

only with Windows/Unix/Linux Version

horizontal partitioning

since Version 11.4

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

with separate tools (MQ, InfoSphere)

Source-replica replication

none

Multi-source replication
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

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

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

yes

fine grained access rights according to SQL-standard

Users and groups

Users with fine-grained authorization concept

no user groups or roles

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