DBMS > Bangdb vs. Ehcache vs. EJDB vs. SQLite vs. UniData,UniVerse

System Properties Comparison Bangdb vs. Ehcache vs. EJDB vs. SQLite vs. UniData,UniVerse

Editorial information provided by DB-Engines

Name

Description

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

A widely adopted Java cache with tiered storage options

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

Widely used embeddable, in-process RDBMS

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Document store
Graph DBMS
Time Series DBMS

Secondary database models

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	4.64
Rank	#68	Overall
	#8	Key-value stores

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	2.85
Rank	#98	Overall
	#1	Multivalue DBMS

Website

bangdb.com

www.ehcache.org

github.com/Softmotions/ejdb

www.sqlite.org

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

docs.bangdb.com

www.ehcache.org/documentation

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

www.sqlite.org/docs.html

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Sachin Sinha, BangDB

Terracotta Inc, owned by Software AG

Softmotions

Dwayne Richard Hipp

Rocket Software

Initial release

2012

2009

2012

2000

1985

Current release

BangDB 2.0, October 2021

3.10.0, March 2022

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache Version 2; commercial licenses available

Open Source

GPLv2

Open Source

Public Domain

commercial

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

Server operating systems

Linux

All OS with a Java VM

server-less

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

yes

dynamic column types

schema-free

Typing

predefined data types such as float or date

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

yes

string, integer, double, bool, date, object_id

yes

not rigid because of 'dynamic typing' concept.

optional

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

SQL-92 is not fully supported

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

JCache

in-process shared library

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

C
C#
C++
Java
Python

Java

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

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

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

yes

Triggers

yes, Notifications (with Streaming only)

yes

Cache Event Listeners

yes

U2 Basic

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

Sharding

by using Terracotta Server

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

by using Terracotta Server

none

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

Tunable Consistency (Strong, Eventual, Weak)

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

yes

supports JTA and can work as an XA resource

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Read/Write Locking

yes

via file-system locks

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

using a tiered cache-storage approach

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)

Access rights according to SQL-standard and operating system based

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