DBMS > Bangdb vs. BigObject vs. OpenEdge vs. VoltDB

System Properties Comparison Bangdb vs. BigObject vs. OpenEdge vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

Converged and high performance database for device data, events, time series, document and graph

Analytic DBMS for real-time computations and queries

Application development environment with integrated database management system

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	3.51
Rank	#86	Overall
	#46	Relational DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

bangdb.com

bigobject.io

www.progress.com/openedge

www.voltdb.com

Technical documentation

docs.bangdb.com

docs.bigobject.io

documentation.progress.com/output/ua/OpenEdge_latest

docs.voltdb.com

Developer

Sachin Sinha, BangDB

BigObject, Inc.

Progress Software Corporation

VoltDB Inc.

Initial release

2012

2015

1984

2010

Current release

BangDB 2.0, October 2021

OpenEdge 12.2, March 2020

11.3, April 2022

License

Commercial or Open Source

Open Source

BSD 3

commercial

free community edition available

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

C, C++

Java, C++

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

AIX
HP-UX
Linux
Solaris
Windows

Linux
OS X

for development

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

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

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

SQL-like DML and DDL statements

yes

close to SQL 92

yes

only a subset of SQL 99

APIs and other access methods

Proprietary protocol
RESTful HTTP API

fluentd
ODBC
RESTful HTTP API

JDBC
ODBC

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C
C#
C++
Java
Python

Progress proprietary ABL (Advanced Business Language)

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Lua

yes

Java

Triggers

yes, Notifications (with Streaming only)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

none

horizontal partitioning

since Version 11.4

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

none

Source-replica replication

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

Tunable consistency, set CAP knob accordingly

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Read/write lock on objects (tables, trees)

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

Snapshots and command logging

In-memory capabilities

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

yes, run db with in-memory only mode

yes

User concepts

Access control

yes (enterprise version only)

Users and groups

Users and roles with access to stored procedures

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