DBMS > Bangdb vs. ObjectBox vs. Postgres-XL vs. Trafodion

System Properties Comparison Bangdb vs. ObjectBox vs. Postgres-XL vs. Trafodion

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Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Transactional SQL-on-Hadoop DBMS

Primary database model

Document store
Graph DBMS
Time Series DBMS

Object oriented DBMS
Vector DBMS

Relational DBMS

Secondary database models

Spatial DBMS

Time Series DBMS

Document store
Spatial DBMS

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

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS
	#7	Vector DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Website

bangdb.com

github.com/objectbox
objectbox.io

www.postgres-xl.org

trafodion.apache.org

Technical documentation

docs.bangdb.com

docs.objectbox.io

www.postgres-xl.org/documentation

trafodion.apache.org/documentation.html

Developer

Sachin Sinha, BangDB

ObjectBox Limited

Apache Software Foundation, originally developed by HP

Initial release

2012

2017

2014

since 2012, originally named StormDB

2014

Current release

BangDB 2.0, October 2021

4.0 (May 2024)

10 R1, October 2018

2.3.0, February 2019

License

Commercial or Open Source

Open Source

BSD 3

Bindings are released under Apache 2.0

Apache License 2.0

Open Source

Mozilla public license

Open Source

Apache 2.0

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++

C and C++

C++, Java

Server operating systems

Linux

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Linux
macOS

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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

yes, plus "flex" map-like types

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

XML type, but no XML query functionality

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

yes

distributed, parallel query execution

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

Proprietary native API

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

ADO.NET
JDBC
ODBC

Supported programming languages

C
C#
C++
Java
Python

C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Data sync between devices allowing occasional connected databases to work completely offline

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

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

User concepts

Access control

yes (enterprise version only)

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

News

The on-device Vector Database for Android and Java
29 May 2024

Vector search: making sense of search queries
29 May 2024

Python on-device Vector and Object Database for Local AI
28 May 2024

Evolution of search: traditional vs vector search
23 May 2024

On-device Vector Database for Dart/Flutter
21 May 2024

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More resources

Recent citations in the news

ObjectBox Raises $2M in Funding
4 December 2018, FinSMEs

The Megashift Towards Decentralized Edge Computing
27 August 2021, hackernoon.com

provided by Google News

Evaluating HTAP Databases for Machine Learning Applications
2 November 2016, KDnuggets

HP Throws Trafodion Hat into OLTP Hadoop Ring
14 July 2014, Datanami

Low-latency, distributed database architectures are critical for emerging fog applications
7 April 2022, Embedded Computing Design

Apache Software Foundation Releases its 2019 Fiscal Year Report
17 August 2019, Open Source For You

provided by Google News

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