DBMS > Bangdb vs. ObjectBox vs. TimesTen vs. VoltDB vs. Yanza

System Properties Comparison Bangdb vs. ObjectBox vs. TimesTen vs. VoltDB vs. Yanza

Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Extremely fast embedded database for small devices, IoT and Mobile

In-Memory RDBMS compatible to Oracle

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

Time Series DBMS for IoT Applications

Primary database model

Document store
Graph DBMS
Time Series DBMS

Object oriented DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

Time Series 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	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

bangdb.com

objectbox.io

www.oracle.com/database/technologies/related/timesten.html

www.voltdb.com

yanza.com

Technical documentation

docs.bangdb.com

docs.objectbox.io

docs.oracle.com/database/timesten-18.1

docs.voltdb.com

Developer

Sachin Sinha, BangDB

ObjectBox Limited

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

VoltDB Inc.

Yanza

Initial release

2012

2017

1998

2010

2015

Current release

BangDB 2.0, October 2021

11 Release 2 (11.2.2.8.0)

11.3, April 2022

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache License 2.0

commercial

Open Source

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

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

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++

Java, C++

Server operating systems

Linux

Android
iOS
Linux
macOS
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
OS X

for development

Windows

Data scheme

schema-free

yes

schema-free

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.

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

yes

only a subset of SQL 99

APIs and other access methods

Proprietary protocol
RESTful HTTP API

Proprietary native API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Java API
JDBC
RESTful HTTP/JSON API

HTTP API

Supported programming languages

C
C#
C++
Java
Python

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

C
C++
Java
PL/SQL

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

any language that supports HTTP calls

Server-side scripts

Stored procedures

PL/SQL

Java

Triggers

yes, Notifications (with Streaming only)

yes

Timer and event based

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

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

online/offline synchronization between client and server

Multi-source replication
Source-replica replication

none

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

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

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

Data access is serialized by the server

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

by means of logfiles and checkpoints

yes

Snapshots and command logging

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

yes

User concepts

Access control

yes (enterprise version only)

yes

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

More information provided by the system vendor

News

Edge AI: The era of on-device AI
23 April 2024

In-Memory Database Use Cases
15 February 2024

Data Viewer for Objects – announcing ObjectBox Admin
14 November 2023

Vector Databases for Edge AI
9 August 2023

Vector Database Release for Flutter / Dart + Python
13 June 2023

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